Why reinforcement learning plateaus without representation depth (and other key takeaways from NeurIPS 2025)

Why reinforcement learning plateaus without representation depth (and other key takeaways from NeurIPS 2025) ...
EurekAlert!

A reinforcement learning framework for guiding the agent to perform exploration based on clustering

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 ...
EurekAlert!

Evolutionary reinforcement learning promises further advances in machine learning

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

AI trading systems mimicking human bias show higher risk

Reinforcement learning frames trading as a sequential decision-making problem, where an agent observes market conditions, ...
CIO Applications

An In-Depth Exploration of Machine Learning Benefits

The ability of computers to learn on their own by using data is known as machine learning. It is closely related to ...
TechCrunch

The future of deep-reinforcement learning, our contemporary AI superhero

It was not long ago that the world watched World Chess Champion Garry Kasparov lose a decisive match against a supercomputer. IBM’s Deep Blue embodied the state of the art in the late 1990s, when a ...