3 papers
cs.MA2025
Optimistic ε-Greedy Exploration for Cooperative Multi-Agent Reinforcement Learning
Ruoning Zhang, Siying Wang, Wenyu Chen +5
The Centralized Training with Decentralized Execution (CTDE) paradigm is widely used in cooperative multi-agent reinforcement learning. However, conventional methods based on CTDE…
cs.LG2024
Highway Graph to Accelerate Reinforcement Learning
Zidu Yin, Zhen Zhang, Dong Gong +2
Reinforcement Learning (RL) algorithms often struggle with low training efficiency. A common approach to address this challenge is integrating model-based planning algorithms, such…
cs.CL2023
Is Feedback All You Need? Leveraging Natural Language Feedback in Goal-Conditioned Reinforcement Learning
Sabrina McCallum, Max Taylor-Davies, Stefano V. Albrecht +1
Despite numerous successes, the field of reinforcement learning (RL) remains far from matching the impressive generalisation power of human behaviour learning. One possible way to…