Making Friends on the Fly: Advances in Ad Hoc Teamwork

This book is devoted to the encounter and interaction of agents such as robots with other agents and describes how they cooperate with their previously unknown teammates, forming an Ad Hoc team. It presents a new algorithm, PLASTIC, that allows agents to quickly adapt to new teammates by reusing kno...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Barrett, Samuel (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cham : Springer International Publishing : Imprint: Springer, 2015.
Edición:1st ed. 2015.
Colección:Studies in Computational Intelligence, 603
Temas:
Computational intelligence.
Game theory.
System theory.
Control engineering.
Robotics.
Automation.
Artificial intelligence.
Computational Intelligence.
Game Theory.
Complex Systems.
Control, Robotics, Automation.
Artificial Intelligence.
Acceso en línea:Texto Completo

MARC

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100 1 |a Barrett, Samuel.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
245 1 0 |a Making Friends on the Fly: Advances in Ad Hoc Teamwork  |h [electronic resource] /  |c by Samuel Barrett. 
250 |a 1st ed. 2015. 
264 1 |a Cham :  |b Springer International Publishing :  |b Imprint: Springer,  |c 2015. 
300 |a XX, 144 p. 26 illus., 19 illus. in color.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
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490 1 |a Studies in Computational Intelligence,  |x 1860-9503 ;  |v 603 
505 0 |a Introduction -- Problem Description -- Background -- Related Work -- The PLASTIC Algorithms -- Theoretical Analysis of PLASTIC -- Empirical Evaluation -- Discussion and Conclusion. 
520 |a This book is devoted to the encounter and interaction of agents such as robots with other agents and describes how they cooperate with their previously unknown teammates, forming an Ad Hoc team. It presents a new algorithm, PLASTIC, that allows agents to quickly adapt to new teammates by reusing knowledge learned from previous teammates.  PLASTIC is instantiated in both a model-based approach, PLASTIC-Model, and a policy-based approach, PLASTIC-Policy.  In addition to reusing knowledge learned from previous teammates, PLASTIC also allows users to provide expert-knowledge and can use transfer learning (such as the new TwoStageTransfer algorithm) to quickly create models of new teammates when it has some information about its new teammates. The effectiveness of the algorithm is demonstrated on three domains, ranging from multi-armed bandits to simulated robot soccer games. 
650 0 |a Computational intelligence. 
650 0 |a Game theory. 
650 0 |a System theory. 
650 0 |a Control engineering. 
650 0 |a Robotics. 
650 0 |a Automation. 
650 0 |a Artificial intelligence. 
650 1 4 |a Computational Intelligence. 
650 2 4 |a Game Theory. 
650 2 4 |a Complex Systems. 
650 2 4 |a Control, Robotics, Automation. 
650 2 4 |a Artificial Intelligence. 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer Nature eBook 
776 0 8 |i Printed edition:  |z 9783319180700 
776 0 8 |i Printed edition:  |z 9783319180687 
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830 0 |a Studies in Computational Intelligence,  |x 1860-9503 ;  |v 603 
856 4 0 |u https://doi.uam.elogim.com/10.1007/978-3-319-18069-4  |z Texto Completo 
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912 |a ZDB-2-SXE 
950 |a Engineering (SpringerNature-11647) 
950 |a Engineering (R0) (SpringerNature-43712) 

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