Tag: Evolved Policy Gradients
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Efficient Last-Iterate Convergence in Constrained MDPs
Discover the PDR-ANPG algorithm for efficient last-iterate convergence in constrained Markov decision processes with improved sample complexity.
Intentional Updates to Improve Streaming Reinforcement Learning
Discover how intentional updates stabilize and enhance streaming reinforcement learning by controlling update magnitudes for better performance.
Discrete Flow Matching Policy Optimization for RL Models
Discover DoMinO, a novel RL framework optimizing discrete flow matching with robust policy gradients and improved sequence generation.
Clarifying Causality in Policy Gradient Derivations
Explore the causality step in policy gradient methods, clarifying the transition from full return to reward-to-go for better reinforcement learning insight...
Complexity-Aware Deep Symbolic Regression with Robust Policy Gradients
Discover a novel deep symbolic regression method using robust risk-seeking policy gradients to improve model robustness and interpretability.