Feb. 9, 2024, 5:43 a.m. | Hafez Ghaemi Hamed Kebriaei Alireza Ramezani Moghaddam Majid Nili Ahamdabadi

cs.LG updates on arXiv.org arxiv.org

Classical multi-agent reinforcement learning (MARL) assumes risk neutrality and complete objectivity for agents. However, in settings where agents need to consider or model human economic or social preferences, a notion of risk must be incorporated into the RL optimization problem. This will be of greater importance in MARL where other human or non-human agents are involved, possibly with their own risk-sensitive policies. In this work, we consider risk-sensitive and non-cooperative MARL with cumulative prospect theory (CPT), a non-convex risk measure …

agent agents cs.ai cs.lg cs.ma economic games human importance markov multi-agent network notion optimization reinforcement reinforcement learning risk social will

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