This project contains the source code and data for the paper titled "Dense reinforcement learning for safety validation of autonomous vehicles". Feng, S., Sun, H ...

This project focuses on applying deep reinforcement learning to acquire a robust policy that allows robots to grasp diverse objects from compact 3D observations in the form of octrees. Evaluation of a ...

Freed from intelligibility and aesthetics, AI designs faster ...

Abstract: In this paper, we consider the problem of multi-cell interference coordination by joint beamforming and power control. Recent efforts have explored the use of reinforcement learning (RL) ...

From autonomous cars to video games, reinforcement learning (machine learning through interaction with environments) can have an important impact. That may feel especially true, for example, when ...

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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 ...

Today's AI agents don't meet the definition of true agents. Key missing elements are reinforcement learning and complex memory. It will take at least five years to get AI agents where they need to be.

Reinforcement learning (RL) is machine learning (ML) in which the learning system adjusts its behavior to maximize the amount of reward and minimize the amount of punishment it receives over time ...

We show that reinforcement learning with verifiable reward using one training example (1-shot RLVR) is effective in incentivizing the mathematical reasoning capabilities of large language models (LLMs ...