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arXiv · 2004.10558

Evolving Dyadic Strategies for a Cooperative Physical Task

Saber Sheybani·Eduardo J. Izquierdo·Eatai Roth
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Abstract

Many cooperative physical tasks require that individuals play specialized roles (e.g., leader-follower). Humans are adept cooperators, negotiating these roles and transitions between roles innately. Yet how roles are delegated and reassigned is not well understood. Using a genetic algorithm, we evolve simulated agents to explore a space of feasible role-switching policies. Applying these switching policies in a cooperative manual task, agents process visual and haptic cues to decide when to switch roles. We then analyze the evolved virtual population for attributes typically associated with cooperation: load sharing and temporal coordination. We find that the best performing dyads exhibit high temporal coordination (anti-synchrony). And in turn, anti-synchrony is correlated to symmetry between the parameters of the cooperative agents. These simulations furnish hypotheses as to how human cooperators might mediate roles in dyadic tasks.

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Saber Sheybani, Eduardo J. Izquierdo, Eatai Roth. 2020-04-22. Evolving Dyadic Strategies for a Cooperative Physical Task. https://arxiv.org/abs/2004.10558

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