Key Points 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.

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Self-driving cars know their own way in unpredictable traffic, thanks to path planning technology. Among current AI-driven ...

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.

There are many different types of reinforcement learning algorithms, but two main categories are “model-based” and “model-free” RL. They are both inspired by our understanding of learning ...

It is a world-renowned institution of higher learning with research activities spanning three campuses, 11 faculties, 13 professional schools, 300 programs of study and over 39,000 students ...

Elephant Learning recognizes the vast potential of adaptive algorithms such as artificial intelligence (AI), as they have revolutionized various industries.

A new generation of reinforcement-learning algorithms could “super quickly pick up in the real world how the environment works,” Albrecht says. But there are some big unsolved problems, Pinto ...