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[null,"1.","Record Nr.",null,"UNINA9911019143403321"]
[null,null,"Titolo",null,"Reinforcement learning and approximate dynamic programming for feedback control / / edited by Frank L. Lewis, Derong Liu"]
[null,null,"Pubbl/distr/stampa",null,"Hoboken, N.J., : IEEE/John Wiley and Sons, Inc., 2013"]
[null,null,"ISBN",null,"1-299-18985-7"]
[{"$nulls":4},"1-118-45393-X"]
[null,null,"Descrizione fisica",null,"1 online resource (643 p.)"]
[null,null,"Collana",null,"IEEE Press series on computational intelligence"]
[null,null,"Classificazione",null,"TEC008000"]
[null,null,"Disciplina",null,"003/.5"]
[null,null,"Soggetti",null,"Reinforcement learning"]
[{"$nulls":4},"Feedback control systems"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Description based upon print version of record."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"pt. 1. Feedback control using RL and ADP -- pt. 2. Learning and control in multiagent games -- pt. 3. Foundations in MDP and RL."]
[null,null,null,"Sommario/riassunto","\"Reinforcement learning (RL) and adaptive dynamic programming (ADP) has been one of the most critical research fields in science and engineering for modern complex systems. This book describes the latest RL and ADP techniques for decision and control in human engineered systems, covering both single player decision and control and multi-player games. Edited by the pioneers of RL and ADP research, the book brings together ideas and methods from many fields and provides an important and timely guidance on controlling a wide variety of systems, such as robots, industrial processes, and economic decision-making\"--"]