10 papers
ConceptTree: Bringing Semantic Transparency to Black-Box Decision Making for Robotic Manipulation
Yongyan Wen, Feifan Liu, Jinyi Chen +3
Establishing interpretable decision-making processes in long-horizon robotic manipulation is critical for enabling reliable human oversight and intervention. However, existing appr…
An HMDP-MPC Decision-making Framework with Adaptive Safety Margins and Hysteresis for Autonomous Driving
Siyuan Li, Chengyuan Liu, Wen-Hua Chen
This paper presents a unified decision-making framework that integrates Hybrid Markov Decision Processes (HMDPs) with Model Predictive Control (MPC), augmented by velocity-dependen…
Hierarchical Decision-Making under Uncertainty: A Hybrid MDP and Chance-Constrained MPC Approach
Siyuan Li, Chengyuan Liu, Wen-Hua Chen
This paper presents a hierarchical decision-making framework for autonomous systems operating under uncertainty, demonstrated through autonomous driving as a representative applica…
GlobeDiff: State Diffusion Process for Partial Observability in Multi-Agent Systems
Yiqin Yang, Xu Yang, Yuhua Jiang +8
In the realm of multi-agent systems, the challenge of \emph{partial observability} is a critical barrier to effective coordination and decision-making. Existing approaches, such as…
Collab-Solver: Collaborative Solving Policy Learning for Mixed-Integer Linear Programming
Siyuan Li, Yifan Yu, Zhihao Zhang +5
Mixed-integer linear programming (MILP) has been a fundamental problem in combinatorial optimization. Conventional MILP solving mainly relies on carefully designed heuristics embed…
MrCoM: A Meta-Regularized World-Model Generalizing Across Multi-Scenarios
Xuantang Xiong, Ni Mu, Runpeng Xie +8
Model-based reinforcement learning (MBRL) is a crucial approach to enhance the generalization capabilities and improve the sample efficiency of RL algorithms. However, current MBRL…