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cs.MA2026
Dreamer-CPC: Message Learning with World Models for Decentralized Multi-agent Reinforcement Learning
Taisuke Takayama, Naoto Yoshida, Tadahiro Taniguchi
In multi-agent reinforcement learning (MARL), inter-agent communication is effective for improving performance under partial observability. Representation learning-based approaches…
cs.MA2025
Reward-Independent Messaging for Decentralized Multi-Agent Reinforcement Learning
Naoto Yoshida, Tadahiro Taniguchi
In multi-agent reinforcement learning (MARL), effective communication improves agent performance, particularly under partial observability. We propose MARL-CPC, a framework that en…
cs.MA2024
Empathic Coupling of Homeostatic States for Intrinsic Prosociality
Naoto Yoshida, Kingson Man
When regarding the suffering of others, we often experience personal distress and feel compelled to help. Inspired by living systems, we investigate the emergence of prosocial beha…