On Evolving Robust Strategies for Iterated Prisoner's Dilemma
AI '93/AI '94 Selected papers from the AI'93 and AI'94 Workshops on Evolutionary Computation, Process in Evolutionary Computation
Behavioral diversity, choices and noise in the iterated prisoner's dilemma
IEEE Transactions on Evolutionary Computation
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Evolutionary games are used to model and understand complex real world situations in economics, defence, and industry. Traditionally, gaming models exhibit interactions among different players or strategies. In the literature, the number of rounds - that a game between different players contains - was treated as an experimental parameter. In this paper, we show for the first time the effect of the number of rounds on the strategic interactions in the Iterated Prisoner's Dilemma. We show that there is a cyclic behavior between the strategies and that the number of rounds per game has a significant affect on the strategies' payoffs, thus the evolutionary process.