#rl-algorithms News & Analysis

2 articles tagged with #rl-algorithms. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

2 articles

AINeutralarXiv – CS AI · Jun 236/10

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Modularized Reinforcement Learning on LLMs: From MDP Creation to Exploration and Learning

A comprehensive survey maps reinforcement learning algorithm design decisions across three stages—MDP creation, exploration strategies, and learning approaches—revealing significant research gaps in LLM training where value-based methods and off-policy techniques remain underexplored despite proven effectiveness in classical RL.

AINeutralarXiv – CS AI · Jun 26/10

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Emergence of Exploration in Policy Gradient Reinforcement Learning via Retrying

Researchers introduce ReMax, a reinforcement learning objective that naturally induces exploration by evaluating policies over multiple samples, and develop RePPO, a PPO variant that achieves exploration without explicit bonus terms. The approach generalizes discrete retry counts to a continuous parameter, enabling fine-grained control of exploration in policy gradient methods.