Reinforcement learning is a type of machine learning that assigns positive or negative values to certain outcomes.

Reinforcement learning is the subset of ML by which an algorithm can be programmed to respond to complex environments for optimal results.

Both deep learning and reinforcement learning are machine learning functions, which in turn are part of a wider set of artificial intelligence tools. What makes deep learning and reinforcement ...

Q-learning is a model-free, value-based, off-policy algorithm for reinforcement learning that will find the best series of actions based on the current state. The “Q” stands for quality.

Reinforcement learning and simulation are essential to solving the constraints and novel challenges that take place in factories and supply chains.

The "reward-is-enough" hypothesis suggests that reinforcement learning alone could lead to AGI.

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 ...

What is Reinforcement Learning? At the core of reinforcement learning is the concept that the optimal behavior or action is reinforced by a positive reward.