TY  - CHAP
AU  - Guojun Zhang
AU  - Haiping Zhu
AU  - Chaoyong Zhang
ED  - 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  - 2024-04-27
ER  -