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03537nam a22005895i 4500 |
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978-3-319-18069-4 |
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DE-He213 |
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20210618024007.0 |
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cr nn 008mamaa |
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150525s2015 gw | s |||| 0|eng d |
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|a 9783319180694
|9 978-3-319-18069-4
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|a 10.1007/978-3-319-18069-4
|2 doi
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|a Q342
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|a Barrett, Samuel.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
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|a Making Friends on the Fly: Advances in Ad Hoc Teamwork
|h [electronic resource] /
|c by Samuel Barrett.
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| 250 |
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|a 1st ed. 2015.
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| 264 |
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1 |
|a Cham :
|b Springer International Publishing :
|b Imprint: Springer,
|c 2015.
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| 300 |
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|a XX, 144 p. 26 illus., 19 illus. in color.
|b online resource.
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| 336 |
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
|2 rdacarrier
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|a text file
|b PDF
|2 rda
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|a Studies in Computational Intelligence,
|x 1860-949X ;
|v 603
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| 505 |
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|a Introduction -- Problem Description -- Background -- Related Work -- The PLASTIC Algorithms -- Theoretical Analysis of PLASTIC -- Empirical Evaluation -- Discussion and Conclusion.
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|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.
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|a Computational intelligence.
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| 650 |
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|a Game theory.
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| 650 |
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|a Sociophysics.
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| 650 |
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|a Econophysics.
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|a Robotics.
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|a Automation.
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|a Artificial intelligence.
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| 650 |
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|a Computational Intelligence.
|0 https://scigraph.springernature.com/ontologies/product-market-codes/T11014
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| 650 |
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|a Game Theory, Economics, Social and Behav. Sciences.
|0 https://scigraph.springernature.com/ontologies/product-market-codes/M13011
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| 650 |
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|a Data-driven Science, Modeling and Theory Building.
|0 https://scigraph.springernature.com/ontologies/product-market-codes/P33030
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| 650 |
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|a Robotics and Automation.
|0 https://scigraph.springernature.com/ontologies/product-market-codes/T19020
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| 650 |
2 |
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|a Artificial Intelligence.
|0 https://scigraph.springernature.com/ontologies/product-market-codes/I21000
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| 710 |
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|a SpringerLink (Online service)
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| 773 |
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|t Springer Nature eBook
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| 776 |
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|i Printed edition:
|z 9783319180700
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| 776 |
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|i Printed edition:
|z 9783319180687
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| 776 |
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|i Printed edition:
|z 9783319369211
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| 830 |
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|a Studies in Computational Intelligence,
|x 1860-949X ;
|v 603
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| 856 |
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|u https://doi.org/10.1007/978-3-319-18069-4
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| 912 |
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|a ZDB-2-ENG
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| 912 |
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|a ZDB-2-SXE
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| 950 |
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|a Engineering (SpringerNature-11647)
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| 950 |
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|a Engineering (R0) (SpringerNature-43712)
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