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Risk profile
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"Credit Assignment. While agents can often learn to jointly solve tasks and thus avoid coordination failures, learning is made more challenging in the multi-agent setting due to the problem of credit assignment (Du et al., 2023; Li et al., 2025, see also Section 3.1 on information asymmetries and Section 3.4, which discusses distributional shift). That is, in the presence of other learning agents, it can be unclear which agents’ actions caused a positive or negative outcome to obtain, especially if the environment is complex. Moreover, in multi-principal settings, agents may not have been trained together and therefore need to generalise to new co-players and collaborators based on their prior experience (Agapiou et al., 2022; Leibo et al., 2021; Stone et al., 2010)."
Suggested mitigations
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Source
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Included resource
Multi-Agent Risks from Advanced AI
Original source
MIT AI Risk Repository
Open the public repository used for AI risk records and taxonomy fields.
