Agent-Specific Effects: A Causal Effect Propagation Analysis in Multi-Agent MDPs

• URL: http://arxiv.org/abs/2310.11334v3
• Date: Mon, 10 Jun 2024 13:01:30 GMT
• Title: Agent-Specific Effects: A Causal Effect Propagation Analysis in Multi-Agent MDPs
• Authors: Stelios Triantafyllou, Aleksa Sukovic, Debmalya Mandal, Goran Radanovic,
• Abstract summary: We introduce agent-specific effects (ASE), a novel causal quantity that measures the effect of an agent's action on the outcome that propagates through other agents. We experimentally evaluate the utility of cf-ASE through a simulation-based testbed, which includes a sepsis management environment.
• Score: 13.524274041966539
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Establishing causal relationships between actions and outcomes is fundamental for accountable multi-agent decision-making. However, interpreting and quantifying agents' contributions to such relationships pose significant challenges. These challenges are particularly prominent in the context of multi-agent sequential decision-making, where the causal effect of an agent's action on the outcome depends on how other agents respond to that action. In this paper, our objective is to present a systematic approach for attributing the causal effects of agents' actions to the influence they exert on other agents. Focusing on multi-agent Markov decision processes, we introduce agent-specific effects (ASE), a novel causal quantity that measures the effect of an agent's action on the outcome that propagates through other agents. We then turn to the counterfactual counterpart of ASE (cf-ASE), provide a sufficient set of conditions for identifying cf-ASE, and propose a practical sampling-based algorithm for estimating it. Finally, we experimentally evaluate the utility of cf-ASE through a simulation-based testbed, which includes a sepsis management environment.

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