FERPO: Forward Entropy-Regularized Policy Optimization

arXiv:2610.02198 · cs.LG, cs.AI, cs.RO, stat.ML · Submitted 2026-10-01 · Read on arXiv

cs.LG, cs.AI, cs.RO, stat.ML

Submitted: 2026-10-01

Updated: 2026-10-01

Code: https://github.com/Atarilab/FERPO

Terminology

• Actor — 79× in this paper · explained in 3 episodes
• Benchmark — 20× in this paper · explained in 2 episodes
• Reinforcement Learning — 19× in this paper · explained in 4 episodes
• Ablation — 14× in this paper · explained in 1 episode
• Regularization — 14× in this paper · explained in 3 episodes
• Accuracy — 7× in this paper · explained in 1 episode
• Forward Entropy-Regularized Policy Optimization — 4× in this paper
• Trace — 4× in this paper · explained in 2 episodes
• Action Space — 3× in this paper · explained in 1 episode
• Allocator — 3× in this paper · explained in 1 episode
• Deep Reinforcement Learning — 3× in this paper · explained in 2 episodes
• KL Regularization — 3× in this paper · explained in 2 episodes
• Relative Entropy Pathwise Policy Optimization — 3× in this paper
• Normalizing Flow — 2× in this paper · explained in 3 episodes
• Pairwise Comparisons — 2× in this paper · explained in 2 episodes
• Aggregation — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Consistency — 1× in this paper · explained in 3 episodes
• Convergence Guarantees — 1× in this paper · explained in 3 episodes
• Diffusion Model — 1× in this paper · explained in 8 episodes
• Diffusion Models — 1× in this paper · explained in 6 episodes
• Embodied AI — 1× in this paper · explained in 2 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Hypernetwork — 1× in this paper · explained in 2 episodes
• Latent Representation — 1× in this paper · explained in 2 episodes
• Normalizing Flows — 1× in this paper · explained in 4 episodes
• Proximal Policy Optimization — 1× in this paper
• Proximal Policy Optimization (PPO) — 1× in this paper · explained in 4 episodes
• Reinforcement Learning (RL) — 1× in this paper · explained in 24 episodes

Sources

• Maximum a Posteriori Policy Optimisation
• Soft Actor-Critic Algorithms and Applications
• AWAC: Accelerating Online Reinforcement Learning with Offline Datasets
• Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning
• Proximal Policy Optimization Algorithms
• FastTD3: Simple, Fast, and Capable Reinforcement Learning for Humanoid Control
• DeepMind Control Suite
• R'enyi Divergence and Kullback-Leibler Divergence

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