Algorithms

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Actor-critic methods

Actor-critic methods are a family of reinforcement learning algorithms that learn two things at once: a parameterized policy, called the actor, which chooses actions, and a value function, called the critic

Deep Learning Machine Learning

Matrix multiplication

Matrix multiplication combines an M by K matrix A with a K by N matrix B to produce an M by N matrix C

AI Hardware Deep Learning

Soft Actor-Critic

Soft Actor-Critic (SAC) is an off-policy, maximum-entropy deep reinforcement learning algorithm that trains a stochastic actor-critic to maximize expected reward plus the entropy of its own policy, so the…

Deep Learning Reinforcement Learning

Twin Delayed DDPG

Twin Delayed Deep Deterministic Policy Gradient (TD3) is an off-policy actor-critic reinforcement learning algorithm for continuous action spaces, introduced by Scott Fujimoto, Herke van Hoof, and David Meger…

Deep Learning Reinforcement Learning