Motion control of humanoid robots is becoming the next hot research area for the application of reinforcement learning (RL) ...

Reinforcement learning focuses on rewarding desired AI actions and punishing undesired ones. Common RL algorithms include State-action-reward-state-action, Q-learning, and Deep-Q networks. RL ...

WiMi's deep reinforcement learning-based task scheduling algorithm in cloud computing includes state representation, action selection, reward function and training and optimization of the algorithm.

This issue has now been addressed. Li Hang's newly launched book 'Machine Learning Methods (2nd Edition)' dedicates a chapter ...

Research suggests AI trading bots can learn to collude without being programmed to do so, potentially driving up your ...

Neuroscientist Daeyeol Lee discusses different modes of reinforcement learning in humans, animals, and AI, and future directions of research.

The application of Deep Reinforcement Learning (DRL) in economics has been an area of active research in recent years. A number of recent works have shown how deep reinforcement learning can be used ...

MILPITAS, Calif.--(BUSINESS WIRE)--Bigfoot Biomedical (Bigfoot), a leader in developing intelligent connected injection support systems, today announced the acquisition of a reinforcement learning ...

A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play David Silver, Thomas Hubert, Julian Schrittwieser, Ioannis Antonogloux, Matthew Lai, Arthur Guez, Marc ...