Reinforcement learning is useful in situations where we want to train AIs to have certain skills we don’t fully understand. We’re going to explore these ideas, introduce a ton of new terms like value, ...

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Nearly a century ago, psychologist B.F. Skinner pioneered a controversial school of thought, behaviorism, to explain human and animal behavior. Behaviorism directly inspired modern reinforcement ...

Chinese robotics player AGIBOT has open-sourced its WORLD 2026 dataset, which focuses on reinforcement ...

Deep Reinforcement Learning (DRL) is a subfield of machine learning that combines neural networks with reinforcement learning techniques to make decisions in complex environments. It has been applied ...

ChatGPT and other AI tools are upending our digital lives, but our AI interactions are about to get physical. Humanoid robots trained with a particular type of AI to sense and react to their world ...

Adversarial attacks against the technique that powers game-playing AIs and could control self-driving cars shows it may be less robust than we thought. The soccer bot lines up to take a shot at the ...

The approach is solid, but the choice of learning rules, circuit architecture, and sparsity assumptions is not always sufficiently justified, and the model would benefit from a clearer mechanistic ...