An information-theoretic model correctly predicts that rats quickly learn an instrumental action despite a 16-min delay to reinforcement, challenging basic assumptions in reinforcement learning ...

Reinforcement Learning (RL) has emerged as a powerful paradigm in machine learning, enabling agents to learn optimal behaviors through interaction with an environment. As the field continues to ...

The goal of this repository is to provide a curated list of resources in Causal Reinforcement Learning (RL). If you have any suggestions (missing papers, tutorials, typos, or amazing blog posts), ...

Mobile robots are playing an increasingly significant role in social life and industrial production, such as searching and rescuing robots, autonomous exploration of sweeping robots, and so on.

RLzoo is a collection of the most practical reinforcement learning algorithms, frameworks and applications. It is implemented with Tensorflow 2.0 and API of neural network layers in TensorLayer2.0+, ...

Humans have the fascinating ability to achieve goals in a complex and constantly changing world, still surpassing modern machine-learning algorithms in terms of flexibility and learning speed. It is ...