fixed Q targets

CellStrat > Research/Blog > fixed Q targets
06
Feb
Policy Gradients – An Introduction

I conducted an Introductory session on Reinforcement Learning Policy Gradients (PG) at CellStrat AI Lab on 1st Feb 2020. The goal of this session was to explain the basic underlying principle of Policy Gradients. The session started off with a quick recap of Reinforcement Learning, so that the audience is well aware of the definitions […]

Posted in: Reinforcement Learning,
Tags: Acrobot, deep Q network, deepmind, DQN, experience replay buffer, fixed Q targets, gradient ascent, openAI Gym, policy based methods, policy gradients, Q learning, reinforcement learning, reward function, rewards based learning, value iteration algorithm,