6 papers
Causal Reinforcement Learning for Complex Card Games: A Magic The Gathering Benchmark
Cristiano da Costa Cunha, Ajmal Mian, Tim French +1
Causal reinforcement learning (RL) lacks benchmarks for complex systems that combine sequential decision making, hidden information, large masked action spaces, and explicit causal…
Maximizing Rollout Informativeness under a Fixed Budget: A Submodular View of Tree Search for Tool-Use Agentic Reinforcement Learning
Yuelin Hu, Zhenbo Yu, Zhengxue Cheng +2
We formalize Rollout Informativeness under a Fixed Budget (RIFB) as the expected non-vanishing policy-gradient mass that a tool-use rollout set injects into Group Relative Policy O…
AGILE: A Comprehensive Workflow for Humanoid Loco-Manipulation Learning
Huihua Zhao, Rafael Cathomen, Lionel Gulich +6
Recent advances in reinforcement learning (RL) have enabled impressive humanoid behaviors in simulation, yet transferring these results to new robots remains challenging. In many r…
UAV Trajectory Optimization via Improved Noisy Deep Q-Network
Zhang Hengyu, Maryam Cheraghy, Liu Wei +3
This paper proposes an Improved Noisy Deep Q-Network (Noisy DQN) to enhance the exploration and stability of Unmanned Aerial Vehicle (UAV) when applying deep reinforcement learning…
Intrinsic-Motivation Multi-Robot Social Formation Navigation with Coordinated Exploration
Hao Fu, Wei Liu, Shuai Zhou
This paper investigates the application of reinforcement learning (RL) to multi-robot social formation navigation, a critical capability for enabling seamless human-robot coexisten…
Robot Crowd Navigation in Dynamic Environment with Offline Reinforcement Learning
Shuai Zhou, Hao Fu, Haodong He +1
Robot crowd navigation has been gaining increasing attention and popularity in various practical applications. In existing research, deep reinforcement learning has been applied to…