Recent years have seen increased interest in the question of whether it is possible to provide an evolutionary game theoretic explanation for certain kinds of social norms. I sketch a proof of a general representation theorem for a large class of evolutionary game theoretic models played on a social network, in hope that this will contribute to a greater understanding of the long-term evolution...

The mechanisms of emergence and evolution collective behaviours in dynamical Multi-Agent Systems (MAS) multiple interacting agents, with diverse behavioral strategies co-presence, have been undergoing mathematical study via Evolutionary Game Theory (EGT). Their systematic also resorts to agent-based modelling simulation (ABM) techniques, thus enabling the aforesaid under a variety conditions, p...

Most examples of the application of evolutionary game theory to problems in biology involve highly simplified models. I contend that it is time to move on and include much more richness in models. In particular, more thought needs to be given to the importance of (i) between-individual variation; (ii) the interaction between individuals, and hence the process by which decisions are reached; (ii...

We begin these lecture notes by a crash course in game theory. In particular, we introduce a fundamental notion of a Nash equilibrium. To address the problem of the equilibrium selection in games with multiple equilibria, we review basic properties of the deterministic replicator dynamics and stochastic dynamics of finite populations. We show the almost global asymptotic stability of an efficie...

In a conference bar a few years ago, I was talking with an economist who specializes in applications of game theory. I mentioned that I was interested in the conceptual problems associated with the assumption that players have common knowledge of their rationality. H is reaction was surprise that anyone still thought seriously about that issue at all. With something like the embarrassment with ...

The task of understanding coevolutionary algorithms is a very difficult one. These algorithms search landscapes which are in some sense adaptive. As a result, the dynamical behaviors of coevolutionary systems can frequently be even more complex than traditional evolutionary algorithms (EAs). Moreover, traditional EA theory tells us little about coevolutionary algorithms. One major question that...