2 papers
cs.AI2024
Explaining an Agent's Future Beliefs through Temporally Decomposing Future Reward Estimators
Mark Towers, Yali Du, Christopher Freeman +1
Future reward estimation is a core component of reinforcement learning agents; i.e., Q-value and state-value functions, predicting an agent's sum of future rewards. Their scalar ou…
cs.MA2024
TAPE: Leveraging Agent Topology for Cooperative Multi-Agent Policy Gradient
Xingzhou Lou, Junge Zhang, Timothy J. Norman +2
Multi-Agent Policy Gradient (MAPG) has made significant progress in recent years. However, centralized critics in state-of-the-art MAPG methods still face the centralized-decentral…