Reinforcement learning has several algorithms that take different approaches to give rewards to the machine.

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.

Q-learning is a popular temporal-difference reinforcement learning algorithm which often explicitly stores state values using lookup tables. This implementation has been proven to converge to the ...

Code freely created in Go from the "Reinforcement Learning - An Introduction" book by Richard S. Sutton and Andrew G. Barto. After attacking deep neural networks in Go, I kept on investigating machine ...

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 ...

What is supervised learning? One last thing you need to know: machine (and deep) learning comes in three flavors: supervised, unsupervised, and reinforcement.