Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2014
ISBN 10: 3659638595 ISBN 13: 9783659638596
Da: preigu, Osnabrück, Germania
EUR 69,45
Quantità: 5 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. Co-evolutionary and Reinforcement Learning Techniques in Computer Go | Some Techniques of Machine Learning Applied to Computer Go | Wester Zela Moraya | Taschenbuch | 276 S. | Englisch | 2014 | LAP LAMBERT Academic Publishing | EAN 9783659638596 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing Nov 2014, 2014
ISBN 10: 3659638595 ISBN 13: 9783659638596
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 82,90
Quantità: 2 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This work models certain processes of nature such as biological evolution and co-evolution as learning processes, and it proposes some techniques that can ensure that these learning processes really occur and can be used to solve certain complex problems such as the game of Go. Go is an ancient and very complex game with simple rules, a game which still presents a challenge for Artificial Intelligence. This work covers certain approaches that can be applied in order to solve this problem, and which are useful for solving other problems, with a proposal to use competitive and cooperative co-evolutionary learning methods and other techniques as suggested by the author. 276 pp. Englisch.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2014
ISBN 10: 3659638595 ISBN 13: 9783659638596
Da: moluna, Greven, Germania
EUR 66,32
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Zela Moraya WesterThe author has a PhD in Computer Science from the UPM in Spain. He won first place in a Competition of Algorithmic Trading with autonomous systems using Machine Learning sponsored by the Madrid Stock Exchange. MSc i.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing Nov 2014, 2014
ISBN 10: 3659638595 ISBN 13: 9783659638596
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
EUR 82,90
Quantità: 1 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This work models certain processes of nature such as biological evolution and co-evolution as learning processes, and it proposes some techniques that can ensure that these learning processes really occur and can be used to solve certain complex problems such as the game of Go. Go is an ancient and very complex game with simple rules, a game which still presents a challenge for Artificial Intelligence. This work covers certain approaches that can be applied in order to solve this problem, and which are useful for solving other problems, with a proposal to use competitive and cooperative co-evolutionary learning methods and other techniques as suggested by the author.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 276 pp. Englisch.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2014
ISBN 10: 3659638595 ISBN 13: 9783659638596
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 82,90
Quantità: 1 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This work models certain processes of nature such as biological evolution and co-evolution as learning processes, and it proposes some techniques that can ensure that these learning processes really occur and can be used to solve certain complex problems such as the game of Go. Go is an ancient and very complex game with simple rules, a game which still presents a challenge for Artificial Intelligence. This work covers certain approaches that can be applied in order to solve this problem, and which are useful for solving other problems, with a proposal to use competitive and cooperative co-evolutionary learning methods and other techniques as suggested by the author.