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Foresight in a Game of Leadership.


ABSTRACT: Leadership can be effective in promoting cooperation within a group, but as the saying goes "heavy is the head that wears the crown". A lot of debate still surrounds exactly what motivates individuals to expend the effort necessary to lead their groupmates. Evolutionary game theoretic models represent individual's thought processes by strategy update protocols. The most common of these are random mutation, individual learning, selective imitation, and myopic optimization. Recently we introduced a new strategy update protocol - foresight - which takes into account future payoffs, and how groupmates respond to one's own strategies. Here we apply our approach to a new 2 × 2 game, where one player, a leader, ensures via inspection and punishment that the other player, a subordinate, produces collective good. We compare the levels of inspection and production predicted by Nash Equilibrium, Quantal Response Equilibrium, level-k cognition, fictitious play, reinforcement learning, selective payoff-biased imitation, and foresight. We show that only foresight and selective imitation are effective at promoting contribution by the subordinate and inspection and punishment by the leader. The role of selective imitation in cultural and social evolution is well appreciated. In line with our prior findings, foresight is a viable alternative route to cooperation.

SUBMITTER: Perry L 

PROVIDER: S-EPMC7010814 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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Foresight in a Game of Leadership.

Perry Logan L   Gavrilets Sergey S  

Scientific reports 20200210 1


Leadership can be effective in promoting cooperation within a group, but as the saying goes "heavy is the head that wears the crown". A lot of debate still surrounds exactly what motivates individuals to expend the effort necessary to lead their groupmates. Evolutionary game theoretic models represent individual's thought processes by strategy update protocols. The most common of these are random mutation, individual learning, selective imitation, and myopic optimization. Recently we introduced  ...[more]

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