# Exploration-Preserving Policy Optimization

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**Published:** 6 октября 2026 г.
**Author:** Hangzhan jin, Mohammad Hamdaqa, Doina Precup
**Source:** arXiv — cs.AI
**Language:** en-US
**HTML:** https://aiqazaqstan.com/ru/articles/exploration-preserving-policy-optimization

Reinforcement learning with verifiable rewards improves reasoning, while the allocation of learning signal shapes which solutions remain accessible under repeated sampling. Group-relative objectives assign equal advantages to equally rewarded responses, making aggregate credit…

> Материал агрегирован из первоисточника: **arXiv — cs.AI**
> [Читать полностью в arXiv — cs.AI](https://arxiv.org/abs/2610.04011)

**Теги:** #arXiv

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