Game Theory, An Introduction

This article provides an introduction to Game Theory, a mathematical framework for analyzing strategic interactions among rational decision-makers. It begins with a historical overview, followed by an explanation of the fundamental concepts and terminology. It then explores the purpose and applications of Game Theory across various fields. The article also pays homage to the luminaries of Game Theory and delves into its sub-disciplines. Finally, it concludes with a list of references and recommendations for further reading, catering to both mathematically adept readers and those with limited mathematical background.

I. Introduction

In the grand tapestry of human intellect, where the interplay of decisions weaves an intricate pattern of consequence and revelation, Game Theory emerges as a beacon of understanding. It is a realm where the mathematical and the strategic converge, where the choices of individuals and collectives are analyzed with the precision of a maestro conducting an orchestra. The symphony thus produced is one of insight, a harmonious understanding of the complex interdependencies that govern the choices we make.

As we embark upon this intellectual odyssey, let us be guided by the spirit of inquiry and the pursuit of knowledge. Let us delve into the depths of Game Theory, exploring its origins, its principles, and its myriad applications. Through the looking glass of Game Theory, we shall glimpse the very fabric of decision-making, woven from the threads of strategy, conflict, and cooperation.

A. Definition of Game Theory

Game Theory stands as a monument to the marriage of mathematics and social science. It is, in essence, the study of strategic interactions among rational decision-makers. These decision-makers, or players, engage in a complex dance, each seeking to maximize their own gains while remaining acutely aware of the choices of others.

The beauty of Game Theory lies in its universality. It is not confined to the games of chance and leisure but extends its reach to the realms of economics, politics, and beyond. It is the prism through which we can view the strategic decisions of nations at war, corporations in competition, and individuals in negotiation.

The cornerstone of Game Theory is the concept of equilibrium, where no player has an incentive to deviate from their chosen strategy given the choices of others. The Nash Equilibrium, named after the illustrious John Nash, is a testament to this concept, illuminating the conditions under which players’ strategies coalesce into a stable state.

B. Brief history and origin of Game Theory

The seeds of Game Theory were sown in the fertile minds of the early 20th century. The venerable John von Neumann, a polymath of unparalleled intellect, was among the first to formalize the concepts that would become Game Theory. Alongside Oskar Morgenstern, he penned Theory of Games and Economic Behavior, a tome that laid the foundation for all future endeavors in this field.

The torch was then passed to John Nash, whose contributions to non-cooperative games are the stuff of legend. The Nash Equilibrium, a concept both elegant and profound, became the linchpin of Game Theory, guiding scholars through the labyrinthine complexities of strategic interaction.

As the decades unfurled, Game Theory blossomed into a discipline of boundless depth and diversity. Scholars from economics, political science, biology, and computer science flocked to its banner, each enriching the field with their unique perspectives and insights.

C. Importance of Game Theory in modern society

Game Theory is the lens through which we discern the patterns of strategic interaction. In economics, it is the guiding hand that shapes market dynamics and competitive behavior. It is the compass by which policymakers navigate the treacherous waters of international relations.

Beyond economics and politics, Game Theory finds its place in the natural world. In biology, it sheds light on the evolutionary strategies of species. In computer science, it informs the design of algorithms and systems.

The importance of Game Theory cannot be overstated. It is the key that unlocks the mysteries of collective decision-making, the map that charts the terrain of strategy and competition.

D. Purpose of this essay and target audience

This essay, dear reader, is a vessel by which you shall traverse the vast seas of Game Theory. It is an invitation to embark upon a journey of discovery, to explore the shores of a discipline that has shaped the very way we understand decision-making and strategy.

The purpose of this essay is threefold. First, to illuminate the hallowed halls of Game Theory, guiding you through its origins and principles. Second, to reveal the myriad applications of Game Theory in the modern world, from the bustling markets of global economics to the intricate dance of international diplomacy. Lastly, to inspire within you a sense of wonder and curiosity, to kindle the flame of intellectual pursuit.

The audience to whom this essay extends its hand is the erudite, the seekers of knowledge who possess a foundation in diverse subjects but may find themselves less versed in the mathematical intricacies. Fear not, for this essay shall be your compass and your guide, navigating the waters of Game Theory with clarity and grace.

It should be noted that, there is a challenge in presenting The History of Game Theory or Understanding the Basics of Game Theory first. Combined, the read was muddy.  Pulling the definitions out resulted in a more interesting journey through history. Unfortunately, that meant presenting terms before they have been clearly defined. Rather than bury the definitions in a glossary or footnotes, I've chosen to provide the basics immediately and succinctly following the history. Feedback from readers has supported this approach most favorably.

Let us then, together, set sail upon these boundless seas. Let us delve into the depths, scale the heights, and emerge with a newfound understanding of the beautiful symphony that is Game Theory.

II. The History of Game Theory

In the vast abundance of human intellect, Game Theory emerges as a symphony of strategic interplay and mathematical elegance. Its history is a rich tapestry woven from the threads of genius, a chronicle of luminaries whose insights have shaped the very fabric of strategic thinking (Myerson, 1991).

As we embark upon this historical odyssey, let us be guided by the spirit of inquiry and the pursuit of knowledge. From the early inklings of strategic thought to the modern edifice of Game Theory, we shall traverse the annals of time, bearing witness to the evolution of a discipline that has illuminated the complexities of decision-making and strategy (Aumann, 1987).

A. Early concepts and precursors

In the early chapters of this illustrious history, the seeds of Game Theory were sown in the fertile minds of the 18th century. The likes of James Waldegrave and Pierre-Simon Laplace made early forays into the analysis of card games, seeking to discern patterns and strategies through mathematical reasoning (Bernstein, 1996). Waldegrave, in particular, is credited with one of the earliest known analyses of a card game, which he documented in a letter in 1713. Laplace, on the other hand, was more focused on probability theory, which would later become an integral part of Game Theory.

These early endeavors, though rudimentary, were the precursors to what would become a rich and diverse field. The study of games and strategic interactions can be traced back to ancient civilizations, where games of chance and strategy were a testament to human intellect and ingenuity (Davis, 1983). Chess, for instance, an ancient game of strategy, was often used as an allegory for military and political strategy. The mathematical analysis of games, however, began to take shape in the 18th and 19th centuries, as scholars like Laplace and later Charles Dodgson (Lewis Carroll) began to analyze games and voting systems mathematically.

The early 20th century saw the formalization of these concepts, as scholars began to recognize the potential of applying mathematical analysis to strategic interactions. The work of Émile Borel and John von Neumann laid the groundwork for the development of Game Theory as a distinct discipline (Dimand & Dimand, 1996). Borel, a French mathematician, was among the first to formalize the concept of mixed strategies and pondered the existence of strategies that would guarantee wins or at least a draw. His work was, in many ways, a precursor to the minimax theorem later formulated by von Neumann.

John von Neumann's contributions in the early 20th century were pivotal. His 1928 paper “Zur Theorie der Gesellschaftsspiele” (On the Theory of Parlor Games) established the minimax theorem, which is fundamental in the theory of games, particularly in two-player zero-sum games (von Neumann, 1928). This theorem essentially states that in a two-player zero-sum game, there exists a strategy for each player such that neither player can unilaterally change their strategy to improve their outcome.

B. The groundbreaking work of John von Neumann and Oskar Morgenstern

The year 1944 marked a watershed moment in the history of Game Theory. John von Neumann, a polymath of unparalleled intellect, and Oskar Morgenstern, an economist of great repute, penned Theory of Games and Economic Behavior (von Neumann & Morgenstern, 1944). This magnum opus laid the very foundation upon which the edifice of Game Theory was built. This book is a rigorous and analytical exploration of games, which are scenarios where multiple decision-makers, or players, interact. The authors focus on the mathematical structures underlying these interactions, particularly in economic contexts.

The book begins by setting up axioms and postulates that form the basis for the mathematical representation of economic behavior. Von Neumann and Morgenstern focus initially on zero-sum games, where one player's gain is exactly balanced by another's loss. They introduce the Minimax Theorem, which is central to Game Theory, and which describes the optimal strategies in competitive situations.

As the book progresses, von Neumann and Morgenstern discuss the concept of utility, which is used to represent preferences. They introduce Expected Utility Theory, suggesting that decision-makers consider the utility of outcomes and their probabilities, behaving as rational agents aiming to maximize expected utility.

In later sections, the authors extend their analysis to cooperative games, where players have the option to form alliances or coalitions. They introduce the characteristic function to represent the value that coalitions can achieve and explore how payoffs can be distributed among coalition members. Concepts such as the core, the Shapley value, and the bargaining set are introduced as solutions to cooperative games.

In summary, "Theory of Games and Economic Behavior" is a seminal work. It became a beacon, illuminating the path for future scholars. It is the genesis, the moment when Game Theory emerged from the shadows as a discipline in its own right (Leonard, 1994). Through mathematical rigor, von Neumann and Morgenstern laid the groundwork for Game Theory, providing tools for analyzing strategic interactions among decision-makers. This book is essential reading for those interested in the mathematical foundations of Game Theory and its applications in economics.

C. The Prisoner's Dilemma and its significance

In the annals of Game Theory, the Prisoner's Dilemma holds a place of honor. Conceived by Merrill Flood and Melvin Dresher and formalized by Albert W. Tucker, it is a parable of cooperation and conflict, a microcosm of the strategic interactions that pervade human society (Poundstone, 1992).

The Prisoner's Dilemma is a simple yet profound construct. It illustrates the tension between individual rationality and collective welfare, and the often counterintuitive nature of strategic decision-making (Axelrod, 1984). The dilemma is usually presented as a hypothetical scenario involving two individuals who are arrested for a crime they committed together. They are held in separate cells, and each is given the option to either betray the other or remain silent. The payoffs for each decision are structured in such a way that each prisoner faces a conflict between self-interest and mutual benefit.

In the classic version of the Prisoner's Dilemma, if both prisoners remain silent, they both serve a short sentence. If one betrays the other while the other remains silent, the betrayer goes free while the other serves a long sentence. If both betray each other, they both serve a moderately long sentence. The dilemma arises because, from the perspective of each prisoner, betraying the other is the rational choice regardless of what the other does. However, when both follow this logic, they end up with a worse outcome than if they had both remained silent.

The Prisoner's Dilemma has far-reaching implications beyond the criminal justice scenario. It serves as a metaphor for various real-life situations where individuals face similar conflicts between personal incentives and collective benefits. For example, in international relations, countries may face a Prisoner's Dilemma when deciding whether to cooperate on issues such as climate change or arms reduction. Each country may find it individually rational to not cooperate, but if all countries follow this logic, they all end up worse off.

Furthermore, the Prisoner's Dilemma has been instrumental in the study of cooperation and the evolution of social norms. Axelrod (1984) conducted a series of experiments involving iterated versions of the Prisoner's Dilemma, where the same players interact repeatedly. He found that strategies based on reciprocity, such as Tit-for-Tat, which involves mimicking the other player's previous action, were remarkably effective in fostering cooperation. This has implications for understanding how cooperative behavior can emerge even in competitive environments.

This dilemma, in its elegant simplicity, has become a cornerstone of Game Theory. It is a lens through which we can view the complexities of cooperation, competition, and human behavior (Dixit & Nalebuff, 2008).

D. Evolution of Game Theory through the 20th century

As the 20th century progressed, Game Theory evolved into a discipline of boundless depth and diversity (Davis, 1983). This evolution was characterized by the incorporation of more complex and realistic models, as well as the application of Game Theory to a wider range of fields. The mathematical foundations laid by von Neumann and Morgenstern were built upon by a new generation of scholars who sought to explore the intricacies of strategic interaction in various contexts. Among these scholars, John Nash emerged as a figure of paramount importance, whose contributions would shape the trajectory of Game Theory for decades to come.

The work of John Nash, with his eponymous Nash Equilibrium, revolutionized non-cooperative games. His insights into the conditions under which players’ strategies stabilize have had far-reaching implications across economics, political science, and beyond (Nash, 1950). The Nash Equilibrium, a state in which no player has an incentive to deviate from their chosen strategy given the strategies of others, became a central concept in Game Theory. It provided a framework for analyzing the outcomes of strategic interactions in a wide array of settings, from market competition and bargaining to international relations and electoral politics. Nash's work was groundbreaking in that it extended the analysis of equilibria to games where players do not necessarily have opposing interests, and where cooperation is not enforceable.

Furthermore, Nash's contributions to Game Theory were not limited to the concept of equilibrium. He also made significant contributions to the theory of bargaining and cooperative games. His work on the Nash bargaining solution, for example, provided a way to predict the outcome of negotiations between two parties (Nash, 1953). This has been particularly influential in labor economics and international trade negotiations. Moreover, Nash's work laid the groundwork for subsequent developments in Game Theory, including the study of repeated games, evolutionary game theory, and mechanism design. His legacy is one of innovation and insight, and his contributions continue to resonate in the ongoing exploration of strategic interaction in an ever-complex world.

Game Theory also found fertile ground in the field of evolutionary biology, where it was used to model the behavior and interactions of species. This application of Game Theory to biology was a testament to the versatility and universality of the concepts it encompasses. Biologists recognized that the strategic interactions among individuals and species in the natural world, particularly in the context of competition for resources and reproduction, bear striking similarities to the games studied in economics and social sciences. This led to the development of evolutionary game theory, which integrates the principles of Game Theory with the tenets of evolutionary biology.

The concept of evolutionary stable strategies (ESS), introduced by John Maynard Smith and George R. Price, became a cornerstone in the study of natural selection and evolutionary dynamics (Smith & Price, 1973). An evolutionary stable strategy is a strategy that, if adopted by a population in a certain environment, cannot be invaded by any alternative strategy that is initially rare. It is a strategy that proves to be resilient over time and under the pressures of natural selection. This concept has been instrumental in explaining phenomena such as the evolution of altruism, the development of social hierarchies, and the dynamics of predator-prey interactions.

Furthermore, evolutionary game theory has provided insights into the co-evolution of species and the maintenance of genetic diversity within populations. For example, it has been used to analyze the rock-paper-scissors dynamics observed in some ecological systems, where three species interact in a cyclic manner, each one having an advantage over the next. Additionally, evolutionary game theory has been applied to understand human behavior and cultural evolution, bridging the gap between biological and cultural processes. The integration of Game Theory into evolutionary biology has thus enriched both fields, providing a more nuanced understanding of the complex web of interactions that shape the natural world.

Furthermore, the latter half of the 20th century saw the advent of cooperative game theory, where the focus shifted to coalitions and cooperative behavior among players. In contrast to non-cooperative game theory, which primarily deals with the strategic choices of individual players, cooperative game theory explores scenarios where players can form alliances or coalitions and make binding commitments. This branch of game theory has been particularly influential in economics, political science, and operations research, as it provides a framework for analyzing collective action and the allocation of benefits among members of a group.

The Shapley value, introduced by Lloyd Shapley, became a key concept in understanding the distribution of payoffs in cooperative games (Shapley, 1953). The Shapley value assigns a payoff to each player in a cooperative game, reflecting their contribution to the total payoff that the coalition can achieve. It is based on the principle that a player's payoff should be proportional to the average marginal contribution they make to all possible coalitions. The Shapley value has been widely used in various applications, including cost allocation, voting power analysis, and market games. It is celebrated for its fairness properties and its ability to provide stable and equitable solutions in cooperative settings.

In addition to the Shapley value, cooperative game theory encompasses a rich array of concepts and solution concepts, such as the core, the nucleolus, and bargaining sets. The core, for instance, is a set of payoff allocations where no subset of players can achieve a better outcome by forming their own coalition (Gillies, 1953). These concepts have been applied to diverse problems, including coalition formation in politics, resource allocation in supply chains, and revenue sharing in collaborations. Cooperative game theory continues to be a vibrant and evolving field, providing valuable insights into the dynamics of cooperation and collective decision-making in a complex world.

E. Recent developments and applications

As we venture into the 21st century, Game Theory continues to be a vibrant and evolving field. Its tendrils have extended into the realm of computer science, where it informs the design of algorithms and systems. The proliferation of digital technologies and the internet has given rise to complex interactions among autonomous agents, be they human or artificial. These interactions often have strategic elements, as agents seek to maximize their own objectives in environments where the actions of others matter. This has led to the emergence of algorithmic game theory, a subfield that explores the intersection of computer science and economic game theory, and has become particularly prominent (Nisan et al., 2007).

Algorithmic game theory is concerned with the design and analysis of algorithms in strategic environments. One of the central issues in this subfield is the design of mechanisms that can achieve desired outcomes in the presence of self-interested agents. For instance, in online auctions, the auctioneer seeks to maximize revenue, while bidders aim to acquire goods at the lowest possible prices. Mechanism design, a component of algorithmic game theory, deals with the creation of rules and structures for such interactions to achieve specific goals, such as efficiency or fairness (Nisan & Ronen, 2001). Another significant area within algorithmic game theory is the study of the computational aspects of equilibria, exploring how quickly and efficiently equilibria in games can be computed.

Furthermore, algorithmic game theory has applications in network design, social networks, online advertising, and distributed systems. For example, it has been used to model and analyze the behavior of users in social networks, where individuals' decisions to join or leave a network depend on the choices of others (Kleinberg et al., 2008). Additionally, it plays a crucial role in the design of cryptocurrencies and blockchain systems, where consensus mechanisms and incentives are critical. As technology continues to evolve and shape the way we interact, algorithmic game theory will undoubtedly remain at the forefront, providing the tools and frameworks necessary to navigate the complex strategic landscapes of the digital age.

In the realm of economics, mechanism design – often referred to as reverse game theory – has gained prominence. While traditional game theory takes the rules of the game as given and analyzes the strategies that players will adopt, mechanism design takes a reverse approach. It involves designing institutions and rules to achieve specific outcomes in strategic settings. This field is concerned with creating systems that align the incentives of self-interested individuals with socially desirable objectives. The work of Leonid Hurwicz, Eric Maskin, and Roger Myerson in this area was recognized with the Nobel Prize in Economics in 2007 for having laid the foundations of mechanism design theory (Maskin, 2008).

Mechanism design has been particularly influential in the design of markets and allocation systems. For instance, it has been used to design auctions, such as spectrum auctions for allocating radio frequencies to telecommunication companies. In these settings, the auctioneer seeks to allocate resources efficiently and fairly, while bidders aim to acquire resources at favorable prices. Mechanism design helps in formulating auction rules that can achieve efficient allocation while ensuring that participants have incentives to reveal their true valuations (Milgrom, 2004). Another application is in the design of voting systems, where mechanism design can be used to create voting rules that aggregate individual preferences into collective decisions in a way that is resistant to manipulation.

Furthermore, mechanism design has applications beyond economics, including political science, law, and computer science. In political science, it is used to analyze the design of political institutions and electoral systems. In law, it can be applied to the design of legal rules and contracts. In computer science, as part of algorithmic game theory, it plays a crucial role in the design of online platforms and marketplaces. As societies become more complex and the interactions among individuals and institutions more intricate, mechanism design will continue to be an essential tool for creating systems that can effectively harness the power of strategic behavior for the greater good.

Moreover, behavioral game theory, which incorporates insights from psychology into game theoretic models, has emerged as a significant area of research. Traditional game theory often assumes that players are perfectly rational and have complete information, which allows them to make decisions that maximize their utility. However, in reality, human decision-making is often influenced by cognitive biases, emotions, and social factors. Behavioral game theory seeks to understand how human behavior deviates from the classical assumptions of rationality and to build more accurate models of decision-making (Camerer, 2003).

One of the key insights of behavioral game theory is that individuals often use heuristics or rules of thumb in decision-making, especially in complex or uncertain environments. These heuristics can sometimes lead to systematic biases. For example, the concept of loss aversion, where individuals are more sensitive to losses than to gains of the same magnitude, has been integrated into behavioral game theory to explain phenomena such as the endowment effect and risk aversion (Kahneman & Tversky, 1979). Another important concept is that of social preferences, where individuals care not only about their own payoffs but also about fairness and the welfare of others. This has been used to explain cooperative behavior in situations like the Prisoner's Dilemma, where traditional game theory would predict non-cooperation.

Furthermore, behavioral game theory has practical applications in various fields including economics, marketing, policy-making, and finance. For instance, it has been used to design interventions known as “nudges” which aim to steer people towards better decisions without restricting their freedom of choice (Thaler & Sunstein, 2008). In finance, understanding behavioral biases can help explain market anomalies that are not accounted for by traditional theories. As behavioral game theory continues to evolve, it enriches our understanding of human behavior in strategic settings and offers tools for designing institutions and policies that take into account the complexities of human psychology.

Game Theory, with its rich history and diverse applications, remains an indispensable tool in our quest to understand the complex web of strategic interactions that shape the world around us. From its early beginnings to its modern-day incarnations, it is a testament to the power of human intellect and the endless pursuit of knowledge.

III. Understanding the Basics of Game Theory

Before we venture too deeply into the labyrinthine depths of Game Theory, let us pause to acquaint ourselves with the fundamental building blocks of this illustrious discipline. Game Theory, in its essence, is a symphony composed of players, strategies, payoffs, and equilibria (Myerson, 1991). These elements, akin to the notes in a musical composition, come together to create the harmonious interplay that is Game Theory.

Therefore, with the spirit of scholarly pursuit as our guide, let us embark upon a journey through the basic concepts and terminology of Game Theory. Let us unravel the threads that weave together the tapestry of strategic decision-making (Osborne, 2004).

A. Key concepts and terminology

In the realm of Game Theory, there are certain concepts and terms that form the very foundation upon which the edifice of this discipline is built. These concepts, like the pillars of an ancient temple, support and give structure to the complex world of strategic interactions (Rasmusen, 2007).

Players

In the grand theater of Game Theory, players are the protagonists. They are the decision-makers, the entities whose choices and actions shape the course of the game (Osborne, 2004). Players can be individuals, groups, firms, or even nations. Their motivations, preferences, and objectives are central to the game, and it is through their strategic interactions that the outcomes are determined (Myerson, 1991).

Players, in their pursuit of objectives, must weigh their options and make decisions. They must anticipate the actions of others and formulate strategies accordingly. In this intricate dance, each player is both the choreographer and the performer, shaping and being shaped by the game (von Neumann & Morgenstern, 1944).

Strategies

Strategies are the battle plans of the players. They are the set of actions or decisions that players can employ in the pursuit of their objectives (Osborne, 2004). A strategy is a blueprint, a guide that informs the player's actions in various situations within the game (Rasmusen, 2007).

In the realm of Game Theory, strategies can be pure or mixed. A pure strategy involves a single, definitive action, while a mixed strategy involves a probabilistic combination of actions. The choice of strategy is central to the player's success and is contingent upon the actions and strategies of others (Myerson, 1991).

Payoffs

In the symphony of Game Theory, payoffs are the crescendo. They are the rewards or outcomes that players receive as a result of their actions and strategies (Osborne, 2004). Payoffs can be monetary, such as profits or losses, or non-monetary, such as utility or satisfaction (Rasmusen, 2007).

Payoffs are central to the decision-making process. Players, in formulating their strategies, are guided by the pursuit of maximizing their payoffs. The payoff matrix, a tabular representation of the payoffs for different combinations of strategies, is a fundamental tool in analyzing games (von Neumann & Morgenstern, 1944).

Equilibrium

Equilibrium, in the context of Game Theory, is the eye of the storm. It is the state in which no player has an incentive to deviate from their chosen strategy, given the strategies of others (Myerson, 1991). The Nash Equilibrium, named after the illustrious John Nash, is a concept that embodies this idea (Nash, 1950).

Equilibrium is a point of stability, a state in which the strategic interplay of players has settled into a pattern from which there is no incentive to deviate. It is a central concept in GameTheory, providing insights into the outcomes and dynamics of strategic interactions (Osborne, 2004).

B. Types of games

As we delve deeper into the realm of Game Theory, we encounter a diverse array of games, each with its own unique characteristics and nuances (Rasmusen, 2007). These games, like the different movements in a symphony, vary in structure, complexity, and dynamics.

Zero-sum games

In the realm of zero-sum games, the gains of one player are exactly offset by the losses of another (von Neumann & Morgenstern, 1944). It is a duel, a contest where the fortunes of the players are inversely linked. Classic examples include poker and chess, where one player's gain is another's loss (Luce & Raiffa, 1957).

Zero-sum games are characterized by conflict and competition. The strategies and actions of the players are guided by the pursuit of gain at the expense of others. In this arena, the art of strategy is a weapon, wielded in the pursuit of victory (Osborne, 2004).

Non-zero-sum games

In contrast to zero-sum games, non-zero-sum games are characterized by the possibility of mutual gain or loss (Luce & Raiffa, 1957). The players, through cooperation or conflict, can influence the outcomes in a way that benefits or harms all involved (Axelrod, 1984).

The Prisoner's Dilemma, a classic example of a non-zero-sum game, illustrates the tension between individual rationality and collective welfare. In such games, the strategies and actions of players are more nuanced, and the outcomes more varied (Poundstone, 1992).

Cooperative vs. non-cooperative games

Cooperative games are those in which players can form coalitions and make binding agreements (Myerson, 1991). In contrast, non-cooperative games are characterized by the absence of binding agreements, and players act independently to maximize their payoffs (Nash, 1950).

In cooperative games, the focus is on collective action and the distribution of payoffs among coalition members. The Shapley value, for example, is a concept that addresses the allocation of payoffs in cooperative games (Shapley, 1953).

Simultaneous vs. sequential games

Simultaneous games are those in which players make decisions or take actions at the same time (Osborne, 2004). In contrast, sequential games involve players making decisions one after another, with each player observing the actions of those who preceded them (Rasmusen, 2007).

In simultaneous games, players must anticipate the actions of others, as they do not have the benefit of observing their choices. In sequential games, the order of play and the ability to observe others’ actions are central to strategy formulation (Myerson, 1991).

Perfect vs. imperfect information games

Perfect information games are those in which players have complete information about the actions and payoffs of others (Rasmusen, 2007). In imperfect information games, players have incomplete information about the actions or payoffs of others (Harsanyi, 1967).

In perfect information games, the decision-making process is more transparent, as players can base their strategies on complete information. In contrast, imperfect information games involve uncertainty and require players to make decisions based on beliefs or estimates (Osborne, 2004).

C. Simplified examples to illustrate concepts without advanced math

As we conclude this exploration of the basics of Game Theory, let us consider simplified examples that illuminate these concepts without the shroud of advanced mathematics. The Prisoner's Dilemma, for instance, is a parable that illustrates the interplay of strategies, payoffs, and equilibria in a non-zero-sum game (Poundstone, 1992). Through the choices of two prisoners, we glimpse the tension between individual rationality and collective welfare.

Another example is the game of Rock, Paper, Scissors, a simultaneous game where players choose one of three options, and the winner is determined by the rules of the game. This game illustrates the concept of mixed strategies, as players randomize their choices to keep opponents guessing (Osborne, 2004).

Game Theory, with its rich tapestry of concepts and applications, is a discipline that illuminates the complexities of strategic interactions. Through simplified examples and a deep understanding of the fundamental concepts, we can appreciate the beauty and depth of this illustrious field.

IV. The Purpose and Applications of Game Theory

As we ascend the lofty peaks of Game Theory, we behold a vista of boundless possibilities. Game Theory, with its mathematical elegance and strategic depth, is not merely an intellectual curiosity; it is a versatile tool, a compass that guides decision-making across a plethora of disciplines (Dixit & Nalebuff, 2008).

From the bustling markets of global economics to the intricate dance of international diplomacy, from the verdant fields of environmental management to the digital frontiers of artificial intelligence, Game Theory is the lodestar that illuminates the path (Myerson, 2013).

A. Decision-making in economics

In the realm of economics, Game Theory is the alchemist’s stone, transmuting the base metals of data and observation into the gold of insight and understanding (Kreps, 1990). It is a lens through which we can view the complex interplay of supply, demand, competition, and cooperation that governs the economic landscape (Fudenberg & Tirole, 1991).

The concept of Nash equilibrium, for instance, is central to understanding market dynamics. It provides insights into how firms, in their pursuit of profit, make decisions regarding pricing, production, and market entry (Nash, 1950).

Furthermore, Game Theory is instrumental in the study of auctions, bargaining, and contract theory. It sheds light on how individuals and firms make strategic decisions in situations where outcomes are contingent upon the actions of others (Myerson, 1981).

B. Strategy formulation in business and management

In the hallowed halls of business and management, Game Theory is the strategist’s blade, honed to a razor’s edge (Brandenburger & Nalebuff, 1995). It informs the formulation of business strategies, guiding firms in their quest for competitive advantage (Dixit & Nalebuff, 2008).

Game Theory provides insights into competitive dynamics, enabling firms to anticipate the actions of rivals and formulate strategies accordingly. It is instrumental in understanding market competition, product differentiation, and strategic alliances (Porter, 1980).

Moreover, Game Theory is invaluable in supply chain management, where it informs decision-making regarding procurement, production, and distribution in the face of uncertainty and strategic interaction (Cachon & Netessine, 2004).

C. Conflict resolution and negotiation

In the arena of conflict resolution and negotiation, Game Theory is the diplomat’s quill and the general’s baton (Brams, 1990). It provides a framework for understanding the strategic interactions that underlie conflicts and negotiations, whether between individuals, groups, or nations (Raiffa, 1982).

The Prisoner’s Dilemma, for instance, is a parable that illustrates the tension between cooperation and conflict, shedding light on the dynamics of negotiation and the challenges of achieving mutually beneficial outcomes (Axelrod, 1984).

Furthermore, Game Theory informs the design of dispute resolution mechanisms, such as arbitration and mediation, guiding the parties in their strategic interactions and facilitating the resolution of conflicts (Brams & Taylor, 1996).

D. Political science and voting systems

In the august domain of political science, Game Theory is the orator’s eloquence and the statesman’s wisdom (Ordeshook, 1986). It provides insights into the strategic interactions that underlie political processes, from elections and voting to legislative bargaining and coalition formation (Riker, 1962).

Game Theory sheds light on the behavior of voters, candidates, and political parties, illuminating the strategic considerations that shape political outcomes (Downs, 1957). It also informs the design of voting systems, providing insights into the properties and implications of different electoral rules (Arrow, 1950).

E. Environmental and resource management

In the verdant fields of environmental and resource management, Game Theory is the steward’s staff, guiding the sustainable and equitable allocation of nature’s bounty (Finus & Rundshagen, 1998). It provides a framework for understanding the strategic interactions that underlie the management of common-pool resources, such as fisheries, forests, and water (Ostrom, 1990).

Game Theory is instrumental in the design of international environmental agreements, guiding nations in their negotiations and commitments to address global environmental challenges such as climate change (Barrett, 2003).

Furthermore, it informs the design of market-based environmental policies, such as cap-and-trade systems, which harness economic incentives to achieve environmental objectives (Tietenberg, 2006).

F. Behavioral sciences and psychology

In the labyrinthine depths of the human mind, Game Theory is the psychologist’s lantern, illuminating the pathways of decision-making and social interaction (Camerer, 2003). It provides a mathematical framework for understanding human behavior, from individual decision-making to social dynamics (Kahneman & Tversky, 1979).

Behavioral game theory, a subfield that integrates insights from psychology into game theoretic models, seeks to understand how real-world behavior deviates from classical assumptions of rationality (Camerer, Colvin, & Fehr, 2004).

Through experiments and observations, behavioral game theory sheds light on phenomena such as altruism, fairness, and reciprocity, enriching our understanding of human behavior (Fehr & Schmidt, 1999).

G. Applications in computer science and artificial intelligence

In the digital frontiers of computer science and artificial intelligence, Game Theory is the algorithm’s logic and the machine’s learning (Nisan et al., 2007). It informs the design of algorithms for optimization, decision-making, and learning in strategic environments (Leyton-Brown & Shoham, 2008).

In multi-agent systems, Game Theory provides a framework for understanding the interactions between autonomous agents, guiding the design of mechanisms for coordination and cooperation (Shoham & Leyton-Brown, 2009).

Furthermore, Game Theory is central to the field of algorithmic mechanism design, which addresses the design of algorithms and systems in settings where users have strategic incentives (Nisan & Ronen, 2001).

In conclusion, Game Theory, with its mathematical rigor and strategic depth, is a compass that guides decision-making across a myriad of disciplines. From economics to artificial intelligence, it is a beacon that illuminates the complexities of strategic interaction.

V. Who's Who in Game Theory

As we traverse the hallowed halls of Game Theory, we encounter a pantheon of intellectual giants whose insights and innovations have shaped this illustrious discipline (Myerson, 1991). These luminaries, with their profound contributions, have illuminated the path of strategic decision-making, casting light on the intricate interplay of competition and cooperation (Osborne, 2004).

From the pioneering work of John von Neumann and Oskar Morgenstern to the groundbreaking insights of John Nash, from the strategic wisdom of Thomas Schelling to the mathematical elegance of Robert Aumann, these scholars have left an indelible imprint on the field of Game Theory (Dixit & Nalebuff, 2008).

A. John von Neumann

John von Neumann, a polymath of unparalleled brilliance, is one of the founding fathers of Game Theory (Leonard, 2010). His seminal work, "Theory of Games and Economic Behavior," co-authored with Oskar Morgenstern, laid the mathematical foundations of the discipline (von Neumann & Morgenstern, 1944).

Von Neumann's contributions to Game Theory are manifold. He introduced the concept of the minimax theorem, a cornerstone of the theory of zero-sum games. His work on the existence of equilibrium in games, and his insights into the nature of strategic interaction, have had a profound impact on the field (Leonard, 2010).

B. Oskar Morgenstern

Oskar Morgenstern, an economist of great repute, collaborated with von Neumann to pioneer the field of Game Theory (Weintraub, 2002). His work, deeply rooted in economic theory, brought a new perspective to the study of strategic interactions (Morgenstern, 1976).

Morgenstern's contributions to Game Theory, while often overshadowed by those of von Neumann, are significant. His insights into the application of Game Theory to economic behavior, and his emphasis on the importance of strategic interaction in economic decision-making, have left a lasting legacy (Weintraub, 2002).

C. John Nash

John Nash, a mathematician of extraordinary talent, revolutionized the field of Game Theory with his concept of the Nash Equilibrium (Nasar, 1998). His work on non-cooperative games, for which he was awarded the Nobel Prize in Economics, has had far-reaching implications across a range of disciplines (Nash, 1950).

Nash's equilibrium concept, which extends beyond the realm of zero-sum games, provides a framework for understanding the outcomes of strategic interactions in a variety of settings. His work has influenced fields as diverse as economics, political science, biology, and computer science (Nasar, 1998).

D. Thomas Schelling

Thomas Schelling, a Nobel laureate in Economics, made significant contributions to the application of Game Theory to social and political problems (Schelling, 1960). His work on conflict and cooperation, and his insights into the dynamics of bargaining and negotiation, have had a profound impact on the field (Schelling, 1980).

Schelling's work on strategic behavior, particularly in the context of nuclear deterrence, has been instrumental in shaping our understanding of international relations and conflict resolution. His concept of the focal point, a solution that players converge on in the absence of communication, is a key contribution to cooperative game theory (Schelling, 1960).

E. Robert Aumann

Robert Aumann, another Nobel laureate, has made seminal contributions to the theory of repeated games and the study of cooperative game theory (Aumann, 1974). His work on the concept of correlated equilibrium, and his insights intothe role of information in strategic interactions, have significantly advanced the field (Aumann, 1987).

Aumann's work has deepened our understanding of how long-term interactions influence strategy and outcomes. His contributions to cooperative game theory, particularly his work on the core and the Shapley value, have provided valuable tools for analyzing coalition formation and payoff distribution (Aumann & Shapley, 1974).

F. Other notable contributors

Beyond these luminaries, there are numerous other scholars whose contributions have enriched the field of Game Theory. These include Reinhard Selten, who introduced the concept of subgame perfect equilibrium (Selten, 1975); Lloyd Shapley, known for his work on cooperative games and the Shapley value (Shapley, 1953); and John Harsanyi, who developed the theory of games with incomplete information (Harsanyi, 1967).

In conclusion, the field of Game Theory is graced by a pantheon of intellectual giants whose contributions have shaped our understanding of strategic interaction. Their insights continue to illuminate the path of scholarly inquiry, casting light on the intricate dance of competition and cooperation.

VI. Sub-disciplines within Game Theory

As we venture further into the labyrinthine depths of Game Theory, we discover a myriad of sub-disciplines, each a tapestry woven with mathematical threads and strategic insights (Osborne, 2004). These sub-disciplines, like the movements in a symphony, add richness and complexity to the field, expanding its horizons and deepening its impact (Myerson, 1991).

From the evolutionary dance of species to the algorithmic logic of machines, from the behavioral quirks of the human mind to the combinatorial intricacies of abstract games, these sub-disciplines are the tributaries that feed the mighty river of Game Theory (Leyton-Brown & Shoham, 2008).

A. Evolutionary game theory

Evolutionary game theory is a sublime fusion of Game Theory and evolutionary biology (Maynard Smith, 1982). It examines the strategic interactions among populations of agents, often biological entities, whose behaviors evolve over time (Weibull, 1995).

In this realm, the concept of an evolutionary stable strategy (ESS) is central. It is a strategy that, once prevalent in a population, cannot be invaded by a mutant strategy. This concept is instrumental in understanding the evolution of behaviors and strategies in biological populations (Maynard Smith & Price, 1973).

Evolutionary game theory has applications beyond biology. It has been employed in the study of social and economic behaviors, providing insights into how cultural norms and social conventions evolve over time (Gintis, 2000).

B. Behavioral game theory

Behavioral game theory is an enchanting interplay between Game Theory and psychology (Camerer, 2003). It seeks to understand how real-world behavior deviates from the classical assumptions of rationality in strategic interactions (Camerer, Loewenstein, & Rabin, 2004).

This sub-discipline employs experiments to observe human behavior in strategic settings. It sheds light on phenomena such as bounded rationality, altruism, and loss aversion, enriching our understanding of human decision-making (Kahneman & Tversky, 1979).

Behavioral game theory has applications in economics, political science, and business, informing the design of policies and strategies that account for human behavioral biases (Thaler & Sunstein, 2008).

C. Combinatorial game theory

Combinatorial game theory is a realm of abstract beauty, focusing on games of perfect information with no chance moves (Berlekamp, Conway, & Guy, 1982). It is concerned with the mathematical properties of such games and the strategies that players employ.

This sub-discipline is characterized by its combinatorial nature, as it deals with the combinations of moves and positions in games. It has applications in the analysis of board games like chess and Go, and in mathematical puzzles (Nowakowski, 1990).

D. Algorithmic game theory

Algorithmic game theory is the digital alchemy of Game Theory and computer science (Nisan et al., 2007). It addresses the design of algorithms in strategic environments, focusing on computational aspects of games (Roughgarden, 2016).

This sub-discipline is central to the study of multi-agent systems, online auctions, and networked systems. It addresses challenges such as computational efficiency, incentive compatibility, and the design of mechanisms that align individual incentives with social objectives (Leyton-Brown & Shoham, 2008).

E. Stochastic games and Markov Decision Processes

Stochastic games are a mesmerizing interplay of strategy and chance, where the outcomes are influenced by both the players’ actions and random events (Shapley, 1953). Markov Decision Processes (MDPs) are a special case, focusing on decision-making in stochastic environments (Puterman, 1994).

In stochastic games, players must account for the uncertainty introduced by random events. This sub-discipline has applications in economics, operations research, and artificial intelligence, particularly in reinforcement learning (Sutton & Barto, 2018).

F. Cooperative game theory

Cooperative game theory is the study of coalitional behavior, where players can form alliances or coalitions and share the payoffs (Peleg & Sudhölter, 2007). It focuses on the distribution of payoffs within coalitions and the conditions under which coalitions form.

The Shapley value, a concept introduced by Lloyd Shapley, is a central solution concept in cooperative game theory, providing a fair distribution of payoffs among the members of a coalition (Shapley, 1953).

Cooperative game theory has applications in economics, political science, and operations research, particularly in the study of market games, voting systems, and cost allocation problems (Roth, 1988).

G. Brief introduction to each sub-discipline and its applications

In summary, the sub-disciplines within Game Theory are as varied as they are profound. Evolutionary game theory examines the evolution of strategies in biological populations. Behavioral game theory delves into the psychological underpinnings of decision-making. Combinatorial game theory explores the mathematical intricacies of games of perfect information. Algorithmic game theory melds computational algorithms with strategic interactions. Stochastic games and Markov Decision Processes deal with decision-making under uncertainty. Cooperative game theory investigates the formation of coalitions and the distribution of payoffs.

Each of these sub-disciplines adds a unique dimension to Game Theory, enriching its tapestry and expanding its applications. From the natural world to the digital frontier, from the human mind to social institutions, Game Theory is a compass that guides us through the complex landscape of strategic interactions.

VII. Real-world Examples and Case Studies

As we embark upon the final leg of our odyssey through the realm of Game Theory, let us turn our gaze to the tapestry of the real world, where the abstract beauty of mathematical models meets the gritty complexity of human affairs (Dixit & Nalebuff, 2008). Here, in the crucible of reality, Game Theory reveals its true power, as a prism through which we can discern the underlying patterns of strategy and decision-making that shape the world around us (Myerson, 1991).

From the cutthroat competition of the marketplace to the delicate ballet of international diplomacy, from the stewardship of our planet’s resources to the intricate web of social interactions, Game Theory is a compass that guides us through the labyrinth of the real world (Osborne, 2004).

A. Business and market competition

In the bustling bazaars of business and market competition, Game Theory is the merchant's abacus and the strategist's map (Brandenburger & Nalebuff, 1995). It provides insights into competitive strategy, pricing, product differentiation, and market entry (Tirole, 1988).

For instance, in the airline industry, companies employ Game Theory to optimize pricing strategies, taking into account the actions and reactions of competitors (Brueckner, 2003). Similarly, in the realm of auctions, Game Theory informs bidding strategies, as exemplified by the FCC spectrum auctions, where billions of dollars were at stake (Milgrom, 2004).

B. International relations and diplomacy

In the grand theater of international relations and diplomacy, Game Theory is the diplomat's playbook and the statesman's lens (Brams, 1990). It sheds light on the strategic interactions among nations, from trade negotiations to military conflicts (Powell, 1999).

The Cuban Missile Crisis, for example, can be analyzed as a game of brinkmanship, where the United States and the Soviet Union engaged in a high-stakes strategic interaction that could have led to nuclear war (Schelling, 1966).

C. Environmental policy-making

In the verdant realm of environmental policy-making, Game Theory is the ecologist's ledger and the policymaker's gavel (Finus & Rundshagen, 1998). It informs the design of international environmental agreements and the allocation of resources for conservation (Barrett, 2003).

For instance, Game Theory has been employed to analyze the negotiations surrounding the Kyoto Protocol, a landmark international agreement aimed at combating climate change (Carraro & Siniscalco, 1993).

D. Social behavior and public goods

In the intricate tapestry of social behavior and public goods, Game Theory is the sociologist's microscope and the economist's scale (Ostrom, 1990). It provides insights into the provision of public goods, the evolution of social norms, and the dynamics of collective action (Fehr & Gächter, 2000).

The tragedy of the commons, a situation where individuals acting in their own self-interest deplete a shared resource, can be understood through the lens of Game Theory as a social dilemma (Hardin, 1968).

E. Technological innovations and network effects

In the digital domain of technological innovations and network effects, Game Theory is the innovator's blueprint and the entrepreneur's compass (Katz & Shapiro, 1985). It informs the strategies of firms in technology markets, where the value of a product or service is affected by the number of users (Economides, 1996).

For instance, in the battle between Blu-ray and HD DVD formats, Game Theory sheds light on the strategic interactions among consumers, manufacturers, and content providers that ultimately determined the winner (Clements & Ohashi, 2005).

In conclusion, Game Theory, with its mathematical rigor and strategic insights, is a powerful tool for understanding the complex interplay of decisions and interactions that shape the world around us. From the marketplace to the halls of government, from the global stage to our local communities, it offers a window into the underlying patterns and dynamics that govern human affairs.

VIII. Conclusion

As we reach the denouement of our intellectual sojourn through the realm of Game Theory, let us pause to reflect upon the symphony of ideas and insights that have graced our journey (Myerson, 1991). With mathematical elegance and strategic acumen, Game Theory has revealed itself as a master key, unlocking the mysteries of human interaction and strategic decision-making (Osborne, 2004).

From the primordial dance of evolutionary strategies to the digital alchemy of algorithmic game theory, from the cutthroat competition of the marketplace to the delicate ballet of international diplomacy, Game Theory stands as a sentinel, guiding us through the labyrinthine complexities of the world around us (Dixit & Nalebuff, 2008).

A. Recap of key points discussed

We embarked upon our journey with an exploration of the very essence of Game Theory, delving into its history, its purpose, and the pantheon of intellectual giants who shaped its development (von Neumann & Morgenstern, 1944; Nash, 1950). We ventured into the depths of its key concepts, from players and strategies to payoffs and equilibria, and marveled at the diversity of games, from zero-sum to cooperative (Shapley, 1953; Selten, 1975).

We then turned our gaze to the applications of Game Theory, witnessing its impact in the realms of economics, business, politics, environmental policy, and beyond (Brandenburger & Nalebuff, 1995; Barrett, 2003). We paid homage to the luminaries of Game Theory, from John von Neumann to John Nash, and explored the rich tapestry of sub-disciplines that have emerged within its domain (Leonard, 2010; Nasar, 1998).

B. The relevance and impact of Game Theory in various fields

Game Theory, with its mathematical rigor and strategic insights, is not merely an academic curiosity, but a potent force that shapes the world around us (Myerson, 1991). In economics, it informs the strategies of firms and the policies of governments (Tirole, 1988). In international relations, it sheds light on the delicate interplay of diplomacy and conflict (Powell, 1999).

In environmental policy, it guides the stewardship of our planet’s resources (Finus & Rundshagen, 1998). In the realm of technology, it informs the development of algorithms and networks (Nisan et al., 2007). And in the social sciences, it provides insights into human behavior and the evolution of social norms (Gintis, 2000).

C. Encouragement for further exploration and study

As we take our leave of the enchanted realm of Game Theory, let us not view this as an ending, but as a beginning (Osborne, 2004). The world of Game Theory is vast and rich, and there are still many treasures to be discovered, many mysteries to be unraveled.

Let us, therefore, take up the torch of intellectual curiosity and venture forth into the unknown. Let us explore new applications, develop new models, and seek new insights. And let us do so with the knowledge that, in the realm of Game Theory, the possibilities are as boundless as the human imagination.

IX. References and Further Reading

A. List of books, articles, and resources for further study

Theory of Games and Economic Behavior by John von Neumann and Oskar Morgenstern (1944)

This seminal work is the cornerstone of Game Theory, laying the mathematical foundations of the field. It is recommended for those seeking a deep and rigorous understanding of Game Theory's origins.

A Beautiful Mind by Sylvia Nasar (1998)

A biography of John Nash, this book provides an engaging account of the life and contributions of one of Game Theory's most celebrated figures. It offers insights into the human side of mathematical genius.

The Art of Strategy: A Game Theorist's Guide to Success in Business and Life by Avinash Dixit and Barry Nalebuff (2008)

This book provides a practical guide to using Game Theory in real-world situations. It is accessible and offers numerous examples and applications, making it ideal for readers from various backgrounds.

Game Theory Evolving: A Problem-Centered Introduction to Modeling Strategic Interaction by Herbert Gintis (2000)

This book offers an introduction to Game Theory with a focus on modeling and problem-solving. It is suitable for readers interested in the applications of Game Theory in economics and social sciences.

Algorithmic Game Theory edited by Noam Nisan, Tim Roughgarden, Éva Tardos, and Vijay V. Vazirani (2007)

A comprehensive text on the intersection of computer science and Game Theory, this book is recommended for readers interested in the algorithmic and computational aspects of games.

B. Recommendations for accessible materials for readers with limited math background

Rock, Paper, Scissors: Game Theory in Everyday Life by Len Fisher (2008)

This book is a light-hearted and accessible introduction to Game Theory, using everyday examples to explain complex concepts. It is ideal for readers who are new to Game Theory and have limited mathematical background.

The Joy of Game Theory: An Introduction to Strategic Thinking by Presh Talwalkar (2014)

This book is an engaging and accessible introduction to Game Theory, using puzzles and examples to explain strategic thinking. It is suitable for readers looking for a fun and intuitive understanding of Game Theory.

Thinking Strategically: The Competitive Edge in Business, Politics, and Everyday Life by Avinash Dixit and Barry Nalebuff (1991)

This book provides an introduction to strategic thinking and Game Theory without heavy mathematics. It uses real-world examples to illustrate concepts and is recommended for readers seeking practical insights.

Game Theory 101: The Complete Textbook by William Spaniel (2011)

This textbook offers a beginner-friendly introduction to Game Theory, focusing on the concepts and applications without delving into complex mathematics. It is suitable for readers seeking a foundational understanding of the field.

Bibliography:

• Arrow, K. J. (1950). A difficulty in the concept of social welfare. Journal of Political Economy, 58(4), 328-346.
• Aumann, R. J. (1974). Subjectivity and correlation in randomized strategies. Journal of Mathematical Economics, 1(1), 67-96.
• Aumann, R. J. (1987). Correlated equilibrium as an expression of Bayesian rationality. Econometrica: Journal of the Econometric Society, 1-18.
• Aumann, R. J. (1987). Game theory. In The New Palgrave: A Dictionary of Economics, 2, 460-482.
• Aumann, R. J., & Shapley, L. S. (1974). Values of non-atomic games. Princeton University Press.
• Axelrod, R. (1984). The evolution of cooperation. Basic books.
• Barrett, S. (2003). Environment and statecraft: The strategy of environmental treaty-making. Oxford University Press.
• Berlekamp, E. R., Conway, J. H., & Guy, R. K. (1982). Winning ways for your mathematical plays. Academic Press.
• Bernstein, P. L. (1996). Against the gods: The remarkable story of risk. John Wiley & Sons.
• Brams, S. J. (1990). Negotiation games: Applying game theory to bargaining and arbitration. Routledge.
• Brams, S. J., & Taylor, A. D. (1996). Fair division: From cake-cutting to dispute resolution. Cambridge University Press.
• Brandenburger, A. M., & Nalebuff, B. J. (1995). The right game: Use game theory to shape strategy. Harvard Business Review, 73(4), 57-71.
• Brueckner, J. K. (2003). Airline traffic and urban economic development. Urban Studies, 40(8), 1455-1469.
• Cachon, G. P., & Netessine, S. (2004). Game theory in supply chain analysis. In Simchi-Levi, D., Wu, S. D., & Shen, Z. J. M. (Eds.),Handbook of quantitative supply chain analysis (pp. 13-66). Springer.
• Camerer, C. F. (2003). Behavioral game theory: Experiments in strategic interaction. Princeton University Press.
• Camerer, C. F., Loewenstein, G., & Rabin, M. (Eds.). (2004). Advances in behavioral economics. Princeton University Press.
• Carraro, C., & Siniscalco, D. (1993). Strategies for the international protection of the environment. Journal of Public Economics, 52(3), 309-328.
• Clements, M. T., & Ohashi, H. (2005). Indirect network effects and the product cycle: Video games in the US, 1994–2002. The Journal of Industrial Economics, 53(4), 515-542.
• Davis, M. D. (1983). Game theory: A nontechnical introduction. Courier Corporation.
• Dimand, R. W., & Dimand, M. A. (1996). A history of game theory. In A Biographical Dictionary of Women Economists.
• Dixit, A., & Nalebuff, B. (2008). The art of strategy: A game theorist's guide to success in business and life. WW Norton & Company.
• Downs, A. (1957). An economic theory of political action in a democracy. Journal of Political Economy, 65(2), 135-150.
• Economides, N. (1996). The economics of networks. International Journal of Industrial Organization, 14(6), 673-699.
• Fehr, E., & Gächter, S. (2000). Cooperation and punishment in public goods experiments. American Economic Review, 90(4), 980-994.
• Fehr, E., & Schmidt, K. M. (1999). A theory of fairness, competition, and cooperation. The Quarterly Journal of Economics, 114(3), 817-868.
• Finus, M., & Rundshagen, B. (1998). Toward a positive theory of coalition formation and endogenous instrumental choice in global pollution control. Public Choice, 96(1-2), 145-186.
• Fudenberg, D., & Tirole, J. (1991). Game theory. MIT Press.
• Gillies, D. B. (1953). Some theorems on n-person games. Ph.D. Thesis, Princeton University.
• Gintis, H. (2000). Game theory evolving: A problem-centered introduction to modeling strategic interaction. Princeton University Press.
• Hardin, G. (1968). The tragedy of the commons. Science, 162(3859), 1243-1248.
• Harsanyi, J. C. (1967). Games with incomplete information played by “Bayesian” players, I-III. Management Science, 14(3), 159-182.
• Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263-291.
• Katz, M. L., & Shapiro, C. (1985). Network externalities, competition, and compatibility. The American Economic Review, 75(3), 424-440.
• Kleinberg, J., Tardos, É., & Wexler, T. (2008). Strategic network formation with structural holes. ACM SIGecom Exchanges, 7(3), 1-10.
• Kreps, D. M. (1990). Game theory and economic modelling. Oxford University Press.
• Leonard, R. (1994). Reading Cournot, reading Nash: the creation and stabilization of the Nash equilibrium. The Economic Journal, 104(424), 492-511.
• Leonard, R. (2010). Von Neumann, Morgenstern, and the creation of game theory: From chess to social science, 1900-1960. Cambridge University Press.
• Leyton-Brown, K., & Shoham, Y. (2008). Essentials of game theory: A concise, multidisciplinary introduction. Morgan & Claypool Publishers.
• Luce, R. D., & Raiffa, H. (1957). Games and decisions: Introduction and critical survey. Dover Publications.
• Maskin, E. (2008). Mechanism design: How to implement social goals. The American Economic Review, 98(3), 567-576.
• Maynard Smith, J. (1982). Evolution and the theory of games. Cambridge University Press.
• Maynard Smith, J., & Price, G. R. (1973). The logic of animal conflict. Nature, 246(5427), 15-18.
• Milgrom, P. (2004). Putting auction theory to work. Cambridge University Press.
• Morgenstern, O. (1976). The collaboration between Oskar Morgenstern and John von Neumann on the theory of games. Journal of Economic Literature, 14(3), 805-816.
• Myerson, R. B. (1981). Optimal auction design. Mathematics of Operations Research, 6(1), 58-73.
• Myerson, R. B. (1991). Game theory: Analysis of conflict. Harvard University Press.
• Myerson, R. B. (2013). Game theory: Analysis of conflict. Harvard University Press.
• Nasar, S. (1998). A beautiful mind. Simon and Schuster.
• Nash, J. (1950). Equilibrium points in n-person games. Proceedings of the National Academy of Sciences, 36(1), 48-49.
• Nash, J. (1953). Two-person cooperative games. Econometrica: Journal of the Econometric Society, 128-140.
• Nisan, N., & Ronen, A. (2001). Algorithmic mechanism design. Games and Economic Behavior, 35(1-2), 166-196.
• Nisan, N., Roughgarden, T., Tardos, E., & Vazirani, V. V. (Eds.). (2007). Algorithmic game theory. Cambridge University Press.
• Nowakowski, R. J. (Ed.). (1990). Games of no chance. Cambridge University Press.
• Ordeshook, P. C. (1986). Game theory and political theory. Cambridge University Press.
• Osborne, M. J. (2004). An introduction to game theory. Oxford University Press.
• Ostrom, E. (1990). Governing the commons: The evolution of institutions for collective action. Cambridge University Press.
• Peleg, B., & Sudhölter, P. (2007). Introduction to the theory of cooperative games. Springer Science & Business Media.
• Porter, M. E. (1980). Competitive strategy: Techniques for analyzing industries and competitors. Free Press.
• Poundstone, W. (1992). Prisoner's Dilemma: John von Neumann, Game Theory, and the Puzzle of the Bomb. Anchor.
• Powell, R. (1999). In the shadow of power: States and strategies in international politics. Princeton University Press.
• Puterman, M. L. (1994). Markov decision processes: Discrete stochastic dynamic programming. John Wiley & Sons.
• Raiffa, H. (1982). The art and science of negotiation. Harvard University Press.
• Rasmusen, E. (2007). Games and information: An introduction to game theory. Blackwell Publishing.
• Riker, W. H. (1962). The theory of political coalitions. Yale University Press.
• Roth, A. E. (Ed.). (1988). The Shapley value: Essays in honor of Lloyd S. Shapley. Cambridge University Press.
• Roughgarden, T. (2016). Twenty lectures on algorithmic game theory. Cambridge University Press.
• Schelling, T. C. (1960). The strategy of conflict. Harvard University Press.
• Schelling, T. C. (1966). Arms and influence. Yale University Press.
• Schelling, T. C. (1980). The strategy of conflict: Prospectus for a reorientation of game theory. Journal of Conflict Resolution, 24(1), 203-264.
• Selten, R. (1975). Reexamination of the perfectness concept for equilibrium points in extensive games. International Journal of Game Theory, 4(1), 25-55.
• Shapley, L. S. (1953). A value for n-person games. Contributions to the Theory of Games, 2(28), 307-317.
• Shoham, Y., & Leyton-Brown, K. (2009). Multiagent systems: Algorithmic, game-theoretic, and logical foundations. Cambridge University Press.
• Smith, J. M., & Price, G. R. (1973). The logic of animal conflict. Nature, 246(5427), 15-18.
• Sutton, R. S., & Barto, A. G. (2018). Reinforcement learning: An introduction. MIT Press.
• Thaler, R. H., & Sunstein, C. R. (2008). Nudge: Improving decisions about health, wealth, and happiness. Yale University Press.
• Tietenberg, T. (2006). Emissions trading: Principles and practice. Resources for the Future.
• Tirole, J. (1988). The theory of industrial organization. MIT Press.
• Weibull, J. W. (1995). Evolutionary game theory. MIT Press.
• Weintraub, E. R. (2002). How economics became a mathematical science. Duke University Press.
• von Neumann, J., & Morgenstern, O. (1944). Theory of games and economic behavior. Princeton University Press.