Risk-Sensitive Multi-Agent Reinforcement Learning in Network Aggregative Markov Games
The paper introduces ‘Risk-Sensitive Multi-Agent Reinforcement Learning in Network Aggregative Markov Games’. It discusses how classical multi-agent reinforcement learning (MARL) assumes risk neutrality and complete objectivity for agents, which falls…
Continue reading