3 papers
cs.AI2026
Neuro-symbolic Action Masking for Deep Reinforcement Learning
Shuai Han, Mehdi Dastani, Shihan Wang
Deep reinforcement learning (DRL) may explore infeasible actions during training and execution. Existing approaches assume a symbol grounding function that maps high-dimensional st…
cs.LG2025
Credit Assignment and Efficient Exploration based on Influence Scope in Multi-agent Reinforcement Learning
Shuai Han, Mehdi Dastani, Shihan Wang
Training cooperative agents in sparse-reward scenarios poses significant challenges for multi-agent reinforcement learning (MARL). Without clear feedback on actions at each step in…
cs.LG2024
Sample Efficient Reinforcement Learning by Automatically Learning to Compose Subtasks
Shuai Han, Mehdi Dastani, Shihan Wang
Improving sample efficiency is central to Reinforcement Learning (RL), especially in environments where the rewards are sparse. Some recent approaches have proposed to specify rewa…