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

The development of every field relies on a few foundational classic books, and artificial intelligence is no exception.

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 ...

The RL model delivers almost the same cost and efficiency outcomes as the MILP optimizer, but with dramatically lower ...

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.

Wastewater treatment is energy-intensive, with aeration and pumping among the largest cost drivers. The review details how AI ...

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

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 ...