19 citations · 52 across the 11 of their papers we have counts for
6 papers · 1 filter
Gaussian Max-Value Entropy Search for Multi-Agent Bayesian Optimization
Haitong Ma, Tianpeng Zhang, Yixuan Wu +2
We study the multi-agent Bayesian optimization (BO) problem, where multiple agents maximize a black-box function via iterative queries. We focus on Entropy Search (ES), a sample-ef…
Reachability Constrained Reinforcement Learning
Dongjie Yu, Haitong Ma, Shengbo Eben Li +1
Constrained reinforcement learning (CRL) has gained significant interest recently, since safety constraints satisfaction is critical for real-world problems. However, existing CRL…
Learn Zero-Constraint-Violation Policy in Model-Free Constrained Reinforcement Learning
Haitong Ma, Changliu Liu, Shengbo Eben Li +3
In the trial-and-error mechanism of reinforcement learning (RL), a notorious contradiction arises when we expect to learn a safe policy: how to learn a safe policy without enough d…
Joint Synthesis of Safety Certificate and Safe Control Policy using Constrained Reinforcement Learning
Haitong Ma, Changliu Liu, Shengbo Eben Li +2
Safety is the major consideration in controlling complex dynamical systems using reinforcement learning (RL), where the safety certificate can provide provable safety guarantee. A…
Feasible Actor-Critic: Constrained Reinforcement Learning for Ensuring Statewise Safety
Haitong Ma, Yang Guan, Shegnbo Eben Li +3
The safety constraints commonly used by existing safe reinforcement learning (RL) methods are defined only on expectation of initial states, but allow each certain state to be unsa…
Integrated Decision and Control: Towards Interpretable and Computationally Efficient Driving Intelligence
Yang Guan, Yangang Ren, Qi Sun +5
Decision and control are core functionalities of high-level automated vehicles. Current mainstream methods, such as functionality decomposition and end-to-end reinforcement learnin…