About this Research Topic
Game Theory, Complex Systems, and Artificial Intelligence (AI) are increasingly pivotal in bringing together diverse methodologies to understand strategic human and economic behaviors. These interdisciplinary studies harness game theory's robust analytical capabilities across various sectors, from climate policy and financial markets to social behaviors and ecosystems. Despite their broad application scope, significant gaps remain in understanding how these strategies impact real-world systems, particularly in dynamic and unpredictable environments.
This Research Topic aims to enrich the paradigm of human decision-making by integrating insights from game theory, complex systems, and AI to deepen our understanding of human behavior. Contributors are encouraged to tap into empirical data and behavioral experiments to unveil the intricate mechanisms of cooperation and competition among individuals or groups, including the strategic behavior of LLMs. The objectives are to refine predictive models of human behavior, enhance theoretical tools, and deliver empirically tested insights that help navigate complex societal and biological challenges.
We welcome articles addressing, but not limited to, the following themes:
Evolutionary game theory applications within complex systems.
The role of LLMs in simulating human behavior in strategic contexts.
Agent-based models and simulations for strategic decision-making.
Network influences on game-theoretical outcomes.
Game theory's role within social network analysis.
Behavioral experiments deriving tactical human interactions.
Economic and biological implications of game theory.
Dynamics of multi-agent systems.
Game theory in climate change strategies.
We invite researchers from various disciplines—including physicists, computer scientists, AI researchers, behavioral economists, and social scientists—to contribute original research articles, reviews, or theoretical papers that align with the interdisciplinary focus of this issue. Together, we can deepen our understanding of human behavior through the lenses of game theory, complex systems, and AI, ultimately providing valuable insights into real-world phenomena and the capabilities of AI and LLM agents in these contexts.
This Research Topic aims to enrich the paradigm of human decision-making by integrating insights from game theory, complex systems, and AI to deepen our understanding of human behavior. Contributors are encouraged to tap into empirical data and behavioral experiments to unveil the intricate mechanisms of cooperation and competition among individuals or groups, including the strategic behavior of LLMs. The objectives are to refine predictive models of human behavior, enhance theoretical tools, and deliver empirically tested insights that help navigate complex societal and biological challenges.
We welcome articles addressing, but not limited to, the following themes:
Evolutionary game theory applications within complex systems.
The role of LLMs in simulating human behavior in strategic contexts.
Agent-based models and simulations for strategic decision-making.
Network influences on game-theoretical outcomes.
Game theory's role within social network analysis.
Behavioral experiments deriving tactical human interactions.
Economic and biological implications of game theory.
Dynamics of multi-agent systems.
Game theory in climate change strategies.
We invite researchers from various disciplines—including physicists, computer scientists, AI researchers, behavioral economists, and social scientists—to contribute original research articles, reviews, or theoretical papers that align with the interdisciplinary focus of this issue. Together, we can deepen our understanding of human behavior through the lenses of game theory, complex systems, and AI, ultimately providing valuable insights into real-world phenomena and the capabilities of AI and LLM agents in these contexts.
Keywords: Game Theory, Complex Systems, Human Behavior, Multi-agent systems, Agent-based Modelling, Complex Networks, Behavioral Experiments
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
