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Multi-Agent Learning of Reactive Strategies in Iterated Games

Wolfe, James P. et al.
arXiv (All) · Papers
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computer-science-and-game-theoryphysics-and-society
Learning agents, whether humans or algorithms, adapt to one another rather than to a fixed environment. Selfish learning need not produce a good outcome for the group, especially when learners face a social dilemma. The iterated prisoner's dilemma (IPD) is the classical example, but it is usually st
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