Using reinforcement learning to autonomously identify the source of errors for agents in a group mission. (arXiv:2107.09232v3 [cs.RO] UPDATED)

When agents are swarmed to execute a mission, there is often a sudden failure
of some of the agents observed from the command base. Solely relying on the
communication between the command base and the concerning agent, it is
generally difficult to determine whether the failure is caused by actuators
(hypothesis, $h_a$) or sensors (hypothesis, $h_s$) However, by instigating
collusion between the agents, we can pinpoint the cause of the failure, that
is, for $h_a$, we expect to detect corresponding …

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