2026
Improving Stochastic Action-Constrained Reinforcement Learning via Truncated Distributions
AAAI 2026technical
In reinforcement learning (RL), it is often advantageous to consider additional constraints on the action space to ensure safety or action relevance. Existing work on such action-constrained RL faces challenges regarding effective policy updates, computational efficiency, and predictable runtime. R