1 citations · 1 across the 3 of their papers we have counts for
3 papers
Beyond Hard Constraints: Budget-Conditioned Reachability For Safe Offline Reinforcement Learning
Janaka Chathuranga Brahmanage, Akshat Kumar
Sequential decision making using Markov Decision Process underpins many realworld applications. Both model-based and model free methods have achieved strong results in these settin…
Leveraging Constraint Violation Signals For Action-Constrained Reinforcement Learning
Janaka Chathuranga Brahmanage, Jiajing Ling, Akshat Kumar
In many RL applications, ensuring an agent's actions adhere to constraints is crucial for safety. Most previous methods in Action-Constrained Reinforcement Learning (ACRL) employ a…
FlowPG: Action-constrained Policy Gradient with Normalizing Flows
Janaka Chathuranga Brahmanage, Jiajing Ling, Akshat Kumar
Action-constrained reinforcement learning (ACRL) is a popular approach for solving safety-critical and resource-allocation related decision making problems. A major challenge in AC…