Computational testbeds for coordination games
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We propose a decision making process meant to mimic human behavior. This pprocess is implemented with computational agents. We use this computational testbed to run simulations of two coordination games, the minimum-effort coordination game and the battle of the sexes game. We find that the computational agents exhibit behavior similar to human subjects from previous experimental work. We then use the computational testbed to develop experimental hypothses, which are then confirmed in the laboratory using human subjects. In particular, we show that higher cost may actually lead to higher average payoffs in the minimum-effort coordination game.
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