A complete pipeline that can run on a single workstation to train a humanoid robot to walk over rough terrain.

Memento-Skills lets AI agents rewrite their own skills using reinforcement learning, hitting 80% task success vs. 50% for ...

From yellow light logic to pothole avoidance on the roadmap, FSD v14.3 is Tesla's most ambitious supervised driving update in recent memory, and early impressions are already turning heads.

Abstract: Integrating learning-based techniques, especially reinforcement learning, into robotics is promising for solving complex problems in unstructured environments. Most of the existing ...

arXiv: https://arxiv.org/abs/1609.08414 Science and Technology Publications, Lda: http://www.scitepress.org/PublicationsDetail.aspx?ID=%2F+JoYnlE148%3D Please cite ...

Reinforcement learning has become the central approach for language models (LMs) to learn from environmental reward or feedback. In practice, the environmental feedback is usually sparse and delayed.

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Over the past few years, AI systems have become much better at discerning images, generating language, and performing tasks within physical and virtual environments. Yet they still fail in ways that ...

This repository showcases a hybrid control system combining Reinforcement Learning (Q-Learning) and Neural-Fuzzy Systems to dynamically tune a PID controller for an Autonomous Underwater Vehicle (AUV) ...

Researchers at Google Cloud and UCLA have proposed a new reinforcement learning framework that significantly improves the ability of language models to learn very challenging multi-step reasoning ...