Vinod K. Mishra received a Ph.D. 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.

• 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

Vinod K. Mishra received a Ph.D. 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.

• 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

Vinod K. Mishra received a Ph.D. 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.

• 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