Machine learning (ML) might be considered the core subset of artificial intelligence (AI), and reinforcement learning may be the quintessential subset of ML that people imagine when they think of AI.

A new open-access study combines Transformer temporal encoding with proximal policy optimization to personalize long-term ...

Formulate sequential decision-making problems as deterministic decision processes, Markov chains, and finite Markov decision processes. Explain and apply core reinforcement learning concepts, ...

It's important for a robot not just to learn a task optimally, but to complete it without going off the rails of reasonable expectations. Until now, roboticists could have one or the other. Aerospace ...

A new research paper titled “Discovering faster matrix multiplication algorithms with reinforcement learning” was published by researchers at DeepMind. “Here we report a deep reinforcement learning ...

Using a bunch of carrots to train a pony and rider. (Photo by: Education Images/Universal Images Group via Getty Images) Andrew Barto and Richard Sutton are the recipients of the Turing Award for ...

ETH Zurich’s Robotic Systems Lab has showcased its ANYmal-D solving a giant Rubik’s Cube ...

I took Berkeley’s CS 188 course in artificial intelligence years ago, and like most students, I left with only a basic understanding of reinforcement learning. When I began coding and working in the ...

Hyphenate, a company that develops artificial intelligence agents for finance departments, raised $45 million in new funding, ...