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Abstract

Following Axelrod's tournaments for strategies in the repeat-play prisoner's dilemma, we ran a ``tournament of party decision rules'' in a dynamic agent-based model of party competition. We asked researchers to submit rules for selecting party positions in a two-dimensional policy space, pitting each rule against all others in a suite of long-running simulations. The most successful rule combined a number of striking features: satisficing rather than maximizing in the short run, being ``parasitic'' on choices made by successful rules, and being hardwired not to attack other agents using the same rule. In a second suite of simulations in a more evolutionary setting in which the selection probability of a rule was a function of the previous success of agents using the same rule, the rule winning the original tournament pulled even further ahead of the competition.

Keywords

agent-based model computer tournament party competition parties and elections

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A Tournament of Party Decision Rules

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