Q-learning is a model-free reinforcement learning algorithm to learn the value of an action in a particular state. It does not require a model of the...

Reinforcement learning is one of three basic machine learning paradigms, alongside supervised learning and unsupervised learning. Reinforcement learning differs...

The machine learning-based attention method simulates how human attention works by assigning varying levels of importance to different words in a sentence...

Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn...

Deep reinforcement learning (deep RL) is a subfield of machine learning that combines reinforcement learning (RL) and deep learning. RL considers the problem...

In statistics and machine learning, ensemble methods use multiple learning algorithms to obtain better predictive performance than could be obtained from...

A transformer is a deep learning architecture developed by Google and based on the multi-head attention mechanism, proposed in a 2017 paper "Attention...

machine learning. Both statistical estimation and machine learning consider the problem of minimizing an objective function that has the form of a sum: Q (...

consequences of pharmacological manipulations of dopamine on learning. PVLV Q-learning Rescorla–Wagner model State–action–reward–state–action (SARSA)...

Q, or q, is the seventeenth letter of the Latin alphabet, used in the modern English alphabet, the alphabets of other western European languages and others...