# Multi-Principal Assistance Games

@article{Fickinger2020MultiPrincipalAG, title={Multi-Principal Assistance Games}, author={Arnaud Fickinger and Simon Zhuang and Dylan Hadfield-Menell and Stuart J. Russell}, journal={ArXiv}, year={2020}, volume={abs/2007.09540} }

Assistance games (also known as cooperative inverse reinforcement learning games) have been proposed as a model for beneficial AI, wherein a robotic agent must act on behalf of a human principal but is initially uncertain about the humans payoff function. This paper studies multi-principal assistance games, which cover the more general case in which the robot acts on behalf of N humans who may have widely differing payoffs. Impossibility theorems in social choice theory and voting theory can be…

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