The problem of evolution of cooperation and the emergence of collective behavior, which cuts across diverse disciplines like Economics, Physics, Biology, Psychology, and Political, Cognitive and Computer Sciences, is still one of the greatest interdisciplinary challenges that science faces today. Mathematical and simulation techniques from Evolutionary Game Theory have been proven useful to study this problem. To understand the evolutionary mechanisms that promote and maintain cooperative behavior in various societies, it is important to take into account the intrinsic complexity of individuals partaking therein, namely their cognitive and complex decision-making processes. The outcome of many social and economic interactions is defined by not only predictions that individuals make about the behavior and intentions of other individuals, but also the cognitive mechanism that the others adopt to make their decision. Modelling research has shown that the way the decision process is modeled, at different levels of complexity, using different cognitive architectures such as high-order theory of mind, cognitive hierarchy theory, cognitive control or bounded rationality, has varying influence on the equilibrium that can be reached in dynamical
systems.
Abundant evidence exists that shows that humans (and many other species) are capable of complex cognitive skills, viz. theory-of-mind, intention recognition, hypothetical, counterfactual and reactive reasoning, emotion guidance, learning, preferences, commitment and morality. To better understand how these mechanisms make cooperation possible they need to be modeled within the context of evolutionary processes. In other words, we should aim to understand how systems that were successfully developed in Artificial Intelligence and Cognitive Sciences to explain human behavior handle themselves in the light of Darwin’s evolutionary theory.
The purpose of this interdisciplinary Research Topic is to bring together researchers working on various aspects of evolution of cooperation, evolutionary psychology, artificial intelligence and cognitive modelling, thus providing an integrated forum to unite these different research perspectives.
This Research Topic will deepen and clarify the role of cognitive and reasoning skills for the evolution of cooperative behavior and their integration in for instance evolutionary game theory. The results and observations will have important implications for the design of self-organized and distributed multi-agent systems (e.g. multi-robot systems), showing how cognition might influence agent cooperation and coordination, and the extent to which cognition may advantageously be implemented into social agents.
The problem of evolution of cooperation and the emergence of collective behavior, which cuts across diverse disciplines like Economics, Physics, Biology, Psychology, and Political, Cognitive and Computer Sciences, is still one of the greatest interdisciplinary challenges that science faces today. Mathematical and simulation techniques from Evolutionary Game Theory have been proven useful to study this problem. To understand the evolutionary mechanisms that promote and maintain cooperative behavior in various societies, it is important to take into account the intrinsic complexity of individuals partaking therein, namely their cognitive and complex decision-making processes. The outcome of many social and economic interactions is defined by not only predictions that individuals make about the behavior and intentions of other individuals, but also the cognitive mechanism that the others adopt to make their decision. Modelling research has shown that the way the decision process is modeled, at different levels of complexity, using different cognitive architectures such as high-order theory of mind, cognitive hierarchy theory, cognitive control or bounded rationality, has varying influence on the equilibrium that can be reached in dynamical
systems.
Abundant evidence exists that shows that humans (and many other species) are capable of complex cognitive skills, viz. theory-of-mind, intention recognition, hypothetical, counterfactual and reactive reasoning, emotion guidance, learning, preferences, commitment and morality. To better understand how these mechanisms make cooperation possible they need to be modeled within the context of evolutionary processes. In other words, we should aim to understand how systems that were successfully developed in Artificial Intelligence and Cognitive Sciences to explain human behavior handle themselves in the light of Darwin’s evolutionary theory.
The purpose of this interdisciplinary Research Topic is to bring together researchers working on various aspects of evolution of cooperation, evolutionary psychology, artificial intelligence and cognitive modelling, thus providing an integrated forum to unite these different research perspectives.
This Research Topic will deepen and clarify the role of cognitive and reasoning skills for the evolution of cooperative behavior and their integration in for instance evolutionary game theory. The results and observations will have important implications for the design of self-organized and distributed multi-agent systems (e.g. multi-robot systems), showing how cognition might influence agent cooperation and coordination, and the extent to which cognition may advantageously be implemented into social agents.
