Speaker
Description
Classical game theory has trained our intuition about important aspect of social interactions, making it possible to recognize general structures of games played out in complex natural settings. Moving beyond the basic models, we appreciate that games are dynamic in nature, cost and benefits are inherently linked to local interactions, and animal responses are based on previous experiences and adaptive decision-making. Information and the ability to acquire, integrate and restrict it, may alter individual strategies, and influence evolutionary dynamics. I will illustrate this with a model of coevolving mating strategies in social networks and propose a framework for adaptive decision-making in natural environments. Here I consider the cognitive machinery that enables animals to behave autonomously, make predictions about the future and adaptive decisions in real time. May viewing the animal as an agent, with goal-directed rather than purely stimulus-driven cognitive and behavioral control, help integrate our understanding of proximate and ultimate causation?
