The Emergence of Cooperation in Asynchronous Iterated Prisoner’s Dilemma
Part of the
Lecture Notes in Computer Science
book series (LNCS, volume 4247)
The Iterated Prisoners Dilemma (IPD) has received much attention because of its ability to demonstrate altruistic behavior. However, most studies focus on the synchronous case, where players make their decisions simultaneously. As this is implausible in most biological contexts, a more generalized approach is required to study the emergence of altruistic behavior in an evolutionary context. Here, we take previous results and present a generalized Markov model for asynchronous IPD, where both, one, or neither player can make a decision at a given time step. We show that the type of asynchronous timing introduced into the model influences the strategy that dominates. The framework presented here is a more biologically plausible scenario through which to investigate altruistic behavior.
KeywordsEvolutionary Context Altruistic Behavior Stag Hunt Stag Hunt Game Markov Matrix
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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