Artificial Life and Game Theory
Issues regarding the emergence of cooperation and altruism in structured populations have puzzled scientists in a large range of domains. In this context, methods of Statistical Physics combined with concepts of both Graph Theory and Evolutionary Game Theory have been used as simple and powerful tools to describe and analyse the conflict of interest between individuals and groups.
Below we describe some of the main aspects that we have been exploring the field. For more details on the ongoing research, please refer to the publications page.
Spatial evolutionary games in different topologies
We investigate models in which agents are arranged on graphs in such a way that their interactions are restricted to their immediate neighbours. It has been shown that different topologies such as lattices, scale-free graphs, small-world graphs, cycle graphs, star-like graphs and bipartite graphs have a considerable impact on the evolution of cooperation, which also favours the formation of different patterns and phenomena.
Coevolutionary models and dynamic networks
The use of dynamic networks represents a natural upgrade of the traditional spatial games. We have been exploring scenarios in which both the game strategies and the network itself are subject to evolution.
Evolution of cooperation among mobile agents
Mobility plays a vital part as a mechanism for the emergence, promotion, and sustainability of cooperation. Specifically, it can allow altruistic players to overcome the temptation to defect by clustering together and to avoid repeated interactions with selfish players. Mobility is a form of network reciprocity that enables agents to respond to their neighbourhood by moving in the environment; this movement can be random or reactive, local or global. It creates a more realistic framework than some of the traditional, static, spatial models.
The concept of abstention in evolutionary game theory
In many scenarios, agents have the freedom to decide whether to participate in the game. Games such as the optional prisoner’s dilemma and the voluntary public goods game incorporate this concept of voluntary participation by adding a third strategy to the game, allowing agents to not only cooperate or defect but also to abstain from a game interaction. Research has shown that the presence of abstainers in the population can actually protect cooperators against exploitation.
The use of evolutionary algorithms in evolutionary game theory
Evolutionary Game Theory allows us to examine dynamic games, which are centred, not by the idea of rational players, but on the population dynamics. We have been investigating the use of evolutionary algorithms and their representations in the study of population dynamics.