The field called Learning Classifier Systems is populated with romantics. Why shouldn't it be possible for computer programs to adapt, learn, and develop while interacting with their environments? In particular, why not systems that, like organic populations, contain competing, perhaps cooperating, entities evolving together? John Holland was one of the earliest scientists with this vision, at a time when so-called artificial intelligence was in its infancy and mainly concerned with preprogrammed systems that didn't learn. that, like organisms, had sensors, took Instead, Holland envisaged systems actions, and had rich self-generated internal structure and processing. In so doing he foresaw and his work prefigured such present day domains as reinforcement learning and embedded agents that are now displacing the older "standard Af' . One focus was what Holland called "classifier systems" sets of competing rule- like "classifiers", each a hypothesis as to how best to react to some aspect of the environment--or to another rule. The system embracing such a rule "popu- lation" would explore its available actions and responses, rewarding and rating the active rules accordingly. Then "good" classifiers would be selected and re- produced, mutated and even crossed, a la Darwin and genetics, steadily and reliably increasing the system's ability to cope.
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The field called Learning Classifier Systems is populated with romantics. Why shouldn't it be possible for computer programs to adapt, learn, and develop while interacting with their environments In particular, why not systems that, like organic populations, contain competing, perhaps cooperating, entities evolving together John Holland was one of the earliest scientists with this vision, at a time when so-called artificial intelligence was in its infancy and mainly concerned with preprogrammed systems that didn't learn. that, like organisms, had sensors, took Instead, Holland envisaged systems actions, and had rich self-generated internal structure and processing. In so doing he foresaw and his work prefigured such present day domains as reinforcement learning and embedded agents that are now displacing the older 'standard Af' . One focus was what Holland called 'classifier systems': sets of competing rule like 'classifiers', each a hypothesis as to how best to react to some aspect of the environment--or to another rule. The system embracing such a rule 'popu lation' would explore its available actions and responses, rewarding and rating the active rules accordingly. Then 'good' classifiers would be selected and re produced, mutated and even crossed, a la Darwin and genetics, steadily and reliably increasing the system's ability to cope. 316 pp. Englisch. N° de réf. du vendeur 9783642535598
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Brings together recent real-world applications of a machine learning technique whose performance has been greatly improved in recent years and which is experiencing resurgence in interestThe field called Learning Classifier Systems is populated w. N° de réf. du vendeur 5063842
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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -The field called Learning Classifier Systems is populated with romantics. Why shouldn't it be possible for computer programs to adapt, learn, and develop while interacting with their environments In particular, why not systems that, like organic populations, contain competing, perhaps cooperating, entities evolving together John Holland was one of the earliest scientists with this vision, at a time when so-called artificial intelligence was in its infancy and mainly concerned with preprogrammed systems that didn't learn. that, like organisms, had sensors, took Instead, Holland envisaged systems actions, and had rich self-generated internal structure and processing. In so doing he foresaw and his work prefigured such present day domains as reinforcement learning and embedded agents that are now displacing the older 'standard Af' . One focus was what Holland called 'classifier systems': sets of competing rule like 'classifiers', each a hypothesis as to how best to react to some aspect of the environment--or to another rule. The system embracing such a rule 'popu lation' would explore its available actions and responses, rewarding and rating the active rules accordingly. Then 'good' classifiers would be selected and re produced, mutated and even crossed, a la Darwin and genetics, steadily and reliably increasing the system's ability to cope.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 316 pp. Englisch. N° de réf. du vendeur 9783642535598
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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - The field called Learning Classifier Systems is populated with romantics. Why shouldn't it be possible for computer programs to adapt, learn, and develop while interacting with their environments In particular, why not systems that, like organic populations, contain competing, perhaps cooperating, entities evolving together John Holland was one of the earliest scientists with this vision, at a time when so-called artificial intelligence was in its infancy and mainly concerned with preprogrammed systems that didn't learn. that, like organisms, had sensors, took Instead, Holland envisaged systems actions, and had rich self-generated internal structure and processing. In so doing he foresaw and his work prefigured such present day domains as reinforcement learning and embedded agents that are now displacing the older 'standard Af' . One focus was what Holland called 'classifier systems': sets of competing rule like 'classifiers', each a hypothesis as to how best to react to some aspect of the environment--or to another rule. The system embracing such a rule 'popu lation' would explore its available actions and responses, rewarding and rating the active rules accordingly. Then 'good' classifiers would be selected and re produced, mutated and even crossed, a la Darwin and genetics, steadily and reliably increasing the system's ability to cope. N° de réf. du vendeur 9783642535598
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