A Ming-Dynasty (1368–1644) block-printed edition of Romance of Three Kingdom on exhibit at the National Museum of China in Beijing Photo: Yang Lanlan/CSST

Game theory is a discipline that examines strategic interaction mechanisms, which has been widely employed in economics, international relations, and other disciplines. To gain a deeper understanding of the latest research progress of game theory in the context of expanding disciplinary frontiers and emerging technologies such as big data, cloud computing, and artificial intelligence, CSST interviewed Lucas Rentschler, an associate professor of economics from Utah State University, and Christopher Dawe, a scholar from University College London.

Historical context 

“Game theory as an academic field is relatively modern, but the principles of strategic decision-making have been discussed for millennia, including in classical Chinese texts like Sun Tzu’s The Art of War,” Dawe said.

The formal and rapid acceleration of game theory as a field is widely attributed to the seminal 1944 work Theory of Games and Economic Behavior by John von Neumann and Oskar Morgenstern, Dawe continued. Around 1950, mathematician John Nash published two seminal papers that made major contributions to game theory. One of these papers introduced the Nash equilibrium, which is considered the most important concept in game theory. In the 1970s and 80s, game theory gained prominence in academic economics. 

In the 1970s, evolutionary game theory added dynamic modeling of populations. The 1980s saw the rise of experimental economics, testing and refining game theories in laboratory settings. Applications grew in auctions and mechanism design. The 1990s integrated psychology, behavioral economics, and neuroscience, revising overly rational assumptions. “Today, game theory remains an active field of study, covering ever more complex models of strategic interaction,” Dawe noted.

Academic and realistic value 

According to Dawe, game theory has become an invaluable analytical framework across the natural and social sciences due to its ability to model complex strategic decision-making. In the natural sciences, game theory is widely applied in biology and even physics. For instance, evolutionary game theory helps biologists understand competition and cooperation within species. Physics uses game theory to analyze strategic interactions between particles.

In economics, game theory has been fundamental for analyzing competition between firms, bargaining behaviors, auction designs, signaling in markets, and mechanism design. Sociologists utilize game theory to explain phenomena like social network emergence, the evolution of social norms, and collective action problems such as the misuse of common resources. Game theory furnishes sociologists with tools to examine strategic decision-making in social contexts systematically. In psychology, game theoretic techniques help explore cognitive biases and decision-making in settings involving risk, reward, and strategic trade-offs. Legal scholars apply game theory to criminal deterrence, evaluating legal penalties, and designing optimal incentives within justice systems. 

“Game theory has great potential to provide guidance towards more cooperative relationships and reduced conflict,” Rentschler said. A key area where it can contribute is through cooperative game theory and solution concepts like the Shapley value. The Shapley value provides a mathematically fair way to allocate rewards or costs in cooperative multiplayer scenarios to reflect each player’s marginal contribution. By providing an equitable division, it gives players appropriate incentive to collaborate rather than compete. The Shapley value has been applied to guide revenue sharing, cost allocation, voting power analysis, and more. Unlike non-cooperative game theory that focuses on self-interest, cooperative modeling explicitly analyzes how to maximize joint gains from synergy. Of course, positive intentions and good faith efforts by participants are still the key prerequisite. But by formally analyzing incentives, fairness, coalition-building, and misperceptions, game theory provides a valuable toolkit to nurture cooperation and steer parties toward mutually beneficial relationships free of avoidable strife.

Noncooperative game theory furnishes strategic clarity when studying war initiation, risk escalation, bargaining space, asymmetric conflict, alliance politics, and other complex geopolitical phenomena, Rentschler added. It provides analytic rigor to power balancing, signaling, credibility, reputation, and coordination—all central factors in interstate relations. While overly reductive models can miss real-world nuance, noncooperative game theory supplies an essential perspective on adversarial incentives, strategic co-dependence, and equilibrium behaviors. With care to empirical validation and psychological depth, it offers insights to manage conflict and deter aggression. 

Research frontiers

Rentschler pointed out that game theory continues to be an active and evolving field of research, with new extensions and applications constantly emerging. One key trend is the development of evolutionary game theory, which applies game-theoretic modeling to evolving populations. Concepts like evolutionary stable strategies and replicator dynamics provide insights into how cooperation and coordination can emerge. The nascent field of quantum game theory also shows promise, exploring how quantum phenomena like entanglement and superposition could affect strategic decision-making.

Beyond these new variants, game theorists are working to better incorporate real-world aspects of human behavior, such as bounded rationality and psychological biases, Rentschler added. The behavioral approach to game theory aims to improve descriptive accuracy. Mechanism design utilizes game theoretic tools to craft incentives and institutions that achieve specific goals. Network effects are increasingly studied using strategic models. In addition, new game models like extensive form and stochastic games are enabling the analysis of sequential interactions, randomness, and uncertainty. 

In Rentschler’s view, computer science has taken the lead in advancing game theory research across multiple fronts in recent years. Computer scientists are developing algorithms and leveraging machine learning to solve intractable game theoretic models and find equilibria in complex, multi-agent scenarios. Approaches like quantal response equilibrium rely on computational power to incorporate bounded rationality into predictions. In terms of applications, computer scientists employ game theory to model strategic decision-making in contexts like cybersecurity, network design, and mechanism design for computer systems.

Overall, the interactions between game theory and computer science run deep, Rentschler concluded. From computational methods to strategic AI to novel applications like cryptography and consensus protocols, computer scientists are advancing game theory into new territories and providing the computational fuel to tackle ever more complex strategic modeling. Game theory, in turn, provides a paradigm for designing increasingly robust computer systems and understanding machine learning models.