1st Edition

An Introduction to Deep Reinforcement Learning

By Vinod K. Mishra Copyright 2026
204 Pages
by Chapman & Hall

204 Pages
by Chapman & Hall

204 Pages
by Chapman & Hall

The current era of artificial intelligence and machine learning (AIML) tools has transformed the workings of vast swaths of our private, working, and social lives beyond recognition. It has been found that these tools can solve many problems in better and faster ways compared to humans. AIML tools allow machines and related systems to reason and infer almost like humans, and this has deep... Read more

Prologue
1. Introduction
2. Survey of ML
3. Basic Mathematics behind Deep Reinforcement Learning
4. Single-Agent Algorithms
5. Multi-Agent RL (MARL) Algorithms
6. Recent Developments in DRL
7. Applications of RL
Epilogue

Biography

Vinod K. Mishra received his PhD in Theoretical Physics from the State University of New York (SUNY) at Stony Brook. After gaining some academic teaching and research experience, he joined Lucent Technology Bell Labs and later became a research scientist at US Army Research Laboratory. His areas of primary interest are quantum information science, artificial intelligence, and machine learning. He is the author of An Introduction to Quantum Communication and Software Defined Networks.