Evolutionary reinforcement learning is an exciting frontier in machine learning, combining the strengths of two distinct approaches: reinforcement learning and evolutionary computation. In ...

Comparison between clustering-based bonus rewards with novelty alone (η = 1.0) and clustering-based bonus rewards (η = 0.5). Here, the collected states (blue dots) are clustered into 5 clusters and ...

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 ...

The technique, called Reinforcement Learning with Verifiable Rewards with Self-Distillation (RLSD), combines the reliable ...

What if the very techniques we rely on to make AI smarter are actually holding it back? A new study has sent shockwaves through the AI community by challenging the long-held belief that reinforcement ...

Reinforcement-learning algorithms in systems like ChatGPT or Google’s Gemini can work wonders, but they usually need hundreds of thousands of shots at a task before they get good at it. That’s why ...

The ability to make adaptive decisions in uncertain environments is a fundamental characteristic of biological intelligence. Historically, computational ...

A deep dive into the role of variance reduction techniques in reinforcement learning and whether they support exploration or ...

A partnership between a UA psychologist and a Harvard professor has yielded some unexpected insights and discoveries about teenage exploration. UA assistant professor of psychology and cognitive ...