TY - CHAP A1 - Guojun Zhang A2 - Haiping Zhu A3 - Chaoyong Zhang ED1 - Abdelhamid Mellouk Y1 - 2011-01-14 PY - 2011 T1 - Hybrid Intelligent Algorithm for Flexible Job-Shop Scheduling Problem under Uncertainty N2 - Reinforcement Learning (RL) is a very dynamic area in terms of theory and application. This book brings together many different aspects of the current research on several fields associated to RL which has been growing rapidly, producing a wide variety of learning algorithms for different applications. Based on 24 Chapters, it covers a very broad variety of topics in RL and their application in autonomous systems. A set of chapters in this book provide a general overview of RL while other chapters focus mostly on the applications of RL paradigms: Game Theory, Multi-Agent Theory, Robotic, Networking Technologies, Vehicular Navigation, Medicine and Industrial Logistic. BT - Advances in Reinforcement Learning SP - Ch. 19 UR - https://doi.org/10.5772/13195 DO - 10.5772/13195 SN - PB - IntechOpen CY - Rijeka Y2 - 2021-06-15 ER -