This book starts by presenting the basics of reinforcement learning using highly intuitive and easy-to-understand exampl
959 171 22MB
English Pages 203 Year 2019
Table of contents :
1 Introduction to Reinforcement Learning..............1
2 Mathematical and Algorithmic Understanding of Reinforcement Learning..............19
3 Coding the Environment and MDP Solution..............28
4 Temporal Difference Learning SARSA and QLearning..............51
5 QLearning in Code..............64
6 Introduction to Deep Learning..............75
7 Implementation Resources..............89
8 Deep Q Network DQN Double DQN and Dueling DQN..............95