Q-CMAPO: A Quantum-Classical Framework for Balancing Exploration and Exploitation in Multi-Agent Reinforcement Learning
Balancing exploration and exploitation is a central challenge in multi-agent
reinforcement learning (MARL), particularly in dynamic environments where
uncertainty and partial observability complicate coordination among agents.
