Layered learning in multiagent systems : a winning approach to robotic soccer
This book looks at multiagent systems that consist of teams of autonomous agents acting in real-time, noisy, collaborative, and adversarial environments. The book makes four main contributions to the fields of machine learning and multiagent systems.First, it describes an architecture within which a...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Stone, Peter - 1971- [verfasserIn] |
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| Format: |
E-Book |
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| Sprache: |
Englisch |
| Erschienen: |
Cambridge, Massachusetts: MIT Press ; c2000 |
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| Schlagwörter: | |
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| Schlagwörter: |
| Systematik: |
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| Anmerkung: |
Includes bibliographical references (p. [261]-272). - Description based on PDF viewed 12/23/2015 |
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| Umfang: |
1 PDF (xii, 272 pages) ; illustrations. |
| Beschreibung: |
Mode of access: World Wide Web. |
| Weitere Ausgabe: |
Erscheint auch als Druck-Ausgabe Stone, Peter, 1971 -: Layered learning in multiagent systems - Cambridge, Mass. [u.a.] : MIT Press, 2000 |
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| Reihe: |
Intelligent robotics and autonomous agents series |
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| Links: | |
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| ISBN: |
978-0-262-28444-8 |
| Katalog-ID: |
1727349482 |
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9780262284448 ebook 978-0-262-28444-8 (DE-627)1727349482 (DE-599)KEP05511959X (OCoLC)857967378 (MITPRESS)6267440 (EBP)05511959X DE-627 ger DE-627 rda eng 006.3 SEPA ST 308 SEPA rvk (DE-625)rvk/143655: ST 300 SEPA rvk (DE-625)rvk/143650: ST 285 SEPA rvk (DE-625)rvk/143648: 54.72 bkl Stone, Peter 1971- verfasserin aut Layered learning in multiagent systems a winning approach to robotic soccer Peter Stone Cambridge, Massachusetts MIT Press c2000 1 PDF (xii, 272 pages) illustrations. Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Intelligent robotics and autonomous agents series Includes bibliographical references (p. [261]-272). - Description based on PDF viewed 12/23/2015 This book looks at multiagent systems that consist of teams of autonomous agents acting in real-time, noisy, collaborative, and adversarial environments. The book makes four main contributions to the fields of machine learning and multiagent systems.First, it describes an architecture within which a flexible team structure allows member agents to decompose a task into flexible roles and to switch roles while acting. Second, it presents layered learning, a general-purpose machine-learning method for complex domains in which learning a mapping directly from agents' sensors to their actuators is intractable with existing machine-learning methods. Third, the book introduces a new multiagent reinforcement learning algorithm--team-partitioned, opaque-transition reinforcement learning (TPOT-RL)--designed for domains in which agents cannot necessarily observe the state-changes caused by other agents' actions. The final contribution is a fully functioning multiagent system that incorporates learning in a real-time, noisy domain with teammates and adversaries--a computer-simulated robotic soccer team.Peter Stone's work is the basis for the CMUnited Robotic Soccer Team, which has dominated recent RoboCup competitions. RoboCup not only helps roboticists to prove their theories in a realistic situation, but has drawn considerable public and professional attention to the field of intelligent robotics. The CMUnited team won the 1999 Stockholm simulator competition, outscoring its opponents by the rather impressive cumulative score of 110-0. Mode of access: World Wide Web. Robotics Multiagent systems s (DE-588)4304075-5 (DE-627)121632806 (DE-576)211064432 Autonomer Roboter gnd s (DE-588)4389058-1 (DE-627)189373342 (DE-576)211924512 Mehragentensystem gnd (DE-627) 9780262194389 Erscheint auch als Druck-Ausgabe 9780262194389 Erscheint auch als Druck-Ausgabe Stone, Peter, 1971 - Layered learning in multiagent systems Cambridge, Mass. [u.a.] : MIT Press, 2000 XII, 272 S. (DE-627)30617314X (DE-576)08680636X 0262194384 https://ieeexplore.ieee.org/book/6267440 X:MITPRESS Verlag lizenzpflichtig ZDB-37-IEM 2012 GBV_ILN_22 ISIL_DE-18 SYSFLAG_1 GBV_KXP GBV_ILN_22_i22818 GBV_ILN_23 ISIL_DE-830 GBV_ILN_100 ISIL_DE-Ma9 GBV_ILN_370 ISIL_DE-1373 GBV_ILN_2015 ISIL_DE-93 ST 308 Robotics, CAD, CAM, CAE etc. Informatik Monografien Künstliche Intelligenz Robotics, CAD, CAM, CAE etc. (DE-627)1271505975 (DE-625)rvk/143655: (DE-576)201505975 ST 300 Allgemeines Informatik Monografien Künstliche Intelligenz Allgemeines (DE-627)1271119005 (DE-625)rvk/143650: (DE-576)201119005 ST 285 Computer supported cooperative work (CSCW), Groupware Informatik Monografien Software und -entwicklung Computer supported cooperative work (CSCW), Groupware (DE-627)1270877453 (DE-625)rvk/143648: (DE-576)200877453 54.72 Künstliche Intelligenz SEPA (DE-627)10641240X BO 045F 006.3 22 01 0018 3848475545 olrm-h228-MITIEEE zi22818 03-02-21 23 01 0830 3957241049 olr-MIT i z 23-07-21 100 01 3100 4472468158 09 --%%-- eBook MIT Press --%%-- --%%-- OLR-MIT-CEC Vervielfältigungen (z.B. Kopien, Downloads) sind nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. z 30-01-24 370 01 4370 4011222461 olr-ebook mitieee Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. i z 01-12-21 2015 01 DE-93 3740751339 00 --%%-- --%%-- p --%%-- Campuslizenz l01 18-08-20 22 01 0018 Volltextzugang Campus https://ieeexplore.ieee.org/book/6267440 22 01 0018 Nur für Angehörige der Universität Hamburg: Volltextzugang von außerhalb des Campus http://emedien.sub.uni-hamburg.de/han/ieee/ieeexplore.ieee.org/book/6267440 23 01 0830 MIT Press EBook https://ieeexplore.ieee.org/book/6267440 100 01 3100 https://ieeexplore.ieee.org/book/6267440 100 01 3100 für Uniangehörige: Zugang weltweit http://han.med.uni-magdeburg.de/han/mitvia-ieee/ieeexplore.ieee.org/book/6267440 370 01 4370 E-Book: Zugriff im HCU-Netz. Zugriff von außerhalb nur für HCU-Angehörige möglich https://ieeexplore.ieee.org/book/6267440 2015 01 DE-93 https://ieeexplore.ieee.org/book/6267440 23 01 0830 2018-01805, 2018-01806, 2018-01808 22 01 0018 olrm-h228-MITIEEE 23 01 0830 olr-MIT 100 01 3100 OLR-MIT-CEC 370 01 4370 olr-ebook mitieee 370 01 4370 2021.12.01 |
| spelling |
9780262284448 ebook 978-0-262-28444-8 (DE-627)1727349482 (DE-599)KEP05511959X (OCoLC)857967378 (MITPRESS)6267440 (EBP)05511959X DE-627 ger DE-627 rda eng 006.3 SEPA ST 308 SEPA rvk (DE-625)rvk/143655: ST 300 SEPA rvk (DE-625)rvk/143650: ST 285 SEPA rvk (DE-625)rvk/143648: 54.72 bkl Stone, Peter 1971- verfasserin aut Layered learning in multiagent systems a winning approach to robotic soccer Peter Stone Cambridge, Massachusetts MIT Press c2000 1 PDF (xii, 272 pages) illustrations. Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Intelligent robotics and autonomous agents series Includes bibliographical references (p. [261]-272). - Description based on PDF viewed 12/23/2015 This book looks at multiagent systems that consist of teams of autonomous agents acting in real-time, noisy, collaborative, and adversarial environments. The book makes four main contributions to the fields of machine learning and multiagent systems.First, it describes an architecture within which a flexible team structure allows member agents to decompose a task into flexible roles and to switch roles while acting. Second, it presents layered learning, a general-purpose machine-learning method for complex domains in which learning a mapping directly from agents' sensors to their actuators is intractable with existing machine-learning methods. Third, the book introduces a new multiagent reinforcement learning algorithm--team-partitioned, opaque-transition reinforcement learning (TPOT-RL)--designed for domains in which agents cannot necessarily observe the state-changes caused by other agents' actions. The final contribution is a fully functioning multiagent system that incorporates learning in a real-time, noisy domain with teammates and adversaries--a computer-simulated robotic soccer team.Peter Stone's work is the basis for the CMUnited Robotic Soccer Team, which has dominated recent RoboCup competitions. RoboCup not only helps roboticists to prove their theories in a realistic situation, but has drawn considerable public and professional attention to the field of intelligent robotics. The CMUnited team won the 1999 Stockholm simulator competition, outscoring its opponents by the rather impressive cumulative score of 110-0. Mode of access: World Wide Web. Robotics Multiagent systems s (DE-588)4304075-5 (DE-627)121632806 (DE-576)211064432 Autonomer Roboter gnd s (DE-588)4389058-1 (DE-627)189373342 (DE-576)211924512 Mehragentensystem gnd (DE-627) 9780262194389 Erscheint auch als Druck-Ausgabe 9780262194389 Erscheint auch als Druck-Ausgabe Stone, Peter, 1971 - Layered learning in multiagent systems Cambridge, Mass. [u.a.] : MIT Press, 2000 XII, 272 S. (DE-627)30617314X (DE-576)08680636X 0262194384 https://ieeexplore.ieee.org/book/6267440 X:MITPRESS Verlag lizenzpflichtig ZDB-37-IEM 2012 GBV_ILN_22 ISIL_DE-18 SYSFLAG_1 GBV_KXP GBV_ILN_22_i22818 GBV_ILN_23 ISIL_DE-830 GBV_ILN_100 ISIL_DE-Ma9 GBV_ILN_370 ISIL_DE-1373 GBV_ILN_2015 ISIL_DE-93 ST 308 Robotics, CAD, CAM, CAE etc. Informatik Monografien Künstliche Intelligenz Robotics, CAD, CAM, CAE etc. (DE-627)1271505975 (DE-625)rvk/143655: (DE-576)201505975 ST 300 Allgemeines Informatik Monografien Künstliche Intelligenz Allgemeines (DE-627)1271119005 (DE-625)rvk/143650: (DE-576)201119005 ST 285 Computer supported cooperative work (CSCW), Groupware Informatik Monografien Software und -entwicklung Computer supported cooperative work (CSCW), Groupware (DE-627)1270877453 (DE-625)rvk/143648: (DE-576)200877453 54.72 Künstliche Intelligenz SEPA (DE-627)10641240X BO 045F 006.3 22 01 0018 3848475545 olrm-h228-MITIEEE zi22818 03-02-21 23 01 0830 3957241049 olr-MIT i z 23-07-21 100 01 3100 4472468158 09 --%%-- eBook MIT Press --%%-- --%%-- OLR-MIT-CEC Vervielfältigungen (z.B. Kopien, Downloads) sind nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. z 30-01-24 370 01 4370 4011222461 olr-ebook mitieee Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. i z 01-12-21 2015 01 DE-93 3740751339 00 --%%-- --%%-- p --%%-- Campuslizenz l01 18-08-20 22 01 0018 Volltextzugang Campus https://ieeexplore.ieee.org/book/6267440 22 01 0018 Nur für Angehörige der Universität Hamburg: Volltextzugang von außerhalb des Campus http://emedien.sub.uni-hamburg.de/han/ieee/ieeexplore.ieee.org/book/6267440 23 01 0830 MIT Press EBook https://ieeexplore.ieee.org/book/6267440 100 01 3100 https://ieeexplore.ieee.org/book/6267440 100 01 3100 für Uniangehörige: Zugang weltweit http://han.med.uni-magdeburg.de/han/mitvia-ieee/ieeexplore.ieee.org/book/6267440 370 01 4370 E-Book: Zugriff im HCU-Netz. Zugriff von außerhalb nur für HCU-Angehörige möglich https://ieeexplore.ieee.org/book/6267440 2015 01 DE-93 https://ieeexplore.ieee.org/book/6267440 23 01 0830 2018-01805, 2018-01806, 2018-01808 22 01 0018 olrm-h228-MITIEEE 23 01 0830 olr-MIT 100 01 3100 OLR-MIT-CEC 370 01 4370 olr-ebook mitieee 370 01 4370 2021.12.01 |
| allfields_unstemmed |
9780262284448 ebook 978-0-262-28444-8 (DE-627)1727349482 (DE-599)KEP05511959X (OCoLC)857967378 (MITPRESS)6267440 (EBP)05511959X DE-627 ger DE-627 rda eng 006.3 SEPA ST 308 SEPA rvk (DE-625)rvk/143655: ST 300 SEPA rvk (DE-625)rvk/143650: ST 285 SEPA rvk (DE-625)rvk/143648: 54.72 bkl Stone, Peter 1971- verfasserin aut Layered learning in multiagent systems a winning approach to robotic soccer Peter Stone Cambridge, Massachusetts MIT Press c2000 1 PDF (xii, 272 pages) illustrations. Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Intelligent robotics and autonomous agents series Includes bibliographical references (p. [261]-272). - Description based on PDF viewed 12/23/2015 This book looks at multiagent systems that consist of teams of autonomous agents acting in real-time, noisy, collaborative, and adversarial environments. The book makes four main contributions to the fields of machine learning and multiagent systems.First, it describes an architecture within which a flexible team structure allows member agents to decompose a task into flexible roles and to switch roles while acting. Second, it presents layered learning, a general-purpose machine-learning method for complex domains in which learning a mapping directly from agents' sensors to their actuators is intractable with existing machine-learning methods. Third, the book introduces a new multiagent reinforcement learning algorithm--team-partitioned, opaque-transition reinforcement learning (TPOT-RL)--designed for domains in which agents cannot necessarily observe the state-changes caused by other agents' actions. The final contribution is a fully functioning multiagent system that incorporates learning in a real-time, noisy domain with teammates and adversaries--a computer-simulated robotic soccer team.Peter Stone's work is the basis for the CMUnited Robotic Soccer Team, which has dominated recent RoboCup competitions. RoboCup not only helps roboticists to prove their theories in a realistic situation, but has drawn considerable public and professional attention to the field of intelligent robotics. The CMUnited team won the 1999 Stockholm simulator competition, outscoring its opponents by the rather impressive cumulative score of 110-0. Mode of access: World Wide Web. Robotics Multiagent systems s (DE-588)4304075-5 (DE-627)121632806 (DE-576)211064432 Autonomer Roboter gnd s (DE-588)4389058-1 (DE-627)189373342 (DE-576)211924512 Mehragentensystem gnd (DE-627) 9780262194389 Erscheint auch als Druck-Ausgabe 9780262194389 Erscheint auch als Druck-Ausgabe Stone, Peter, 1971 - Layered learning in multiagent systems Cambridge, Mass. [u.a.] : MIT Press, 2000 XII, 272 S. (DE-627)30617314X (DE-576)08680636X 0262194384 https://ieeexplore.ieee.org/book/6267440 X:MITPRESS Verlag lizenzpflichtig ZDB-37-IEM 2012 GBV_ILN_22 ISIL_DE-18 SYSFLAG_1 GBV_KXP GBV_ILN_22_i22818 GBV_ILN_23 ISIL_DE-830 GBV_ILN_100 ISIL_DE-Ma9 GBV_ILN_370 ISIL_DE-1373 GBV_ILN_2015 ISIL_DE-93 ST 308 Robotics, CAD, CAM, CAE etc. Informatik Monografien Künstliche Intelligenz Robotics, CAD, CAM, CAE etc. (DE-627)1271505975 (DE-625)rvk/143655: (DE-576)201505975 ST 300 Allgemeines Informatik Monografien Künstliche Intelligenz Allgemeines (DE-627)1271119005 (DE-625)rvk/143650: (DE-576)201119005 ST 285 Computer supported cooperative work (CSCW), Groupware Informatik Monografien Software und -entwicklung Computer supported cooperative work (CSCW), Groupware (DE-627)1270877453 (DE-625)rvk/143648: (DE-576)200877453 54.72 Künstliche Intelligenz SEPA (DE-627)10641240X BO 045F 006.3 22 01 0018 3848475545 olrm-h228-MITIEEE zi22818 03-02-21 23 01 0830 3957241049 olr-MIT i z 23-07-21 100 01 3100 4472468158 09 --%%-- eBook MIT Press --%%-- --%%-- OLR-MIT-CEC Vervielfältigungen (z.B. Kopien, Downloads) sind nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. z 30-01-24 370 01 4370 4011222461 olr-ebook mitieee Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. i z 01-12-21 2015 01 DE-93 3740751339 00 --%%-- --%%-- p --%%-- Campuslizenz l01 18-08-20 22 01 0018 Volltextzugang Campus https://ieeexplore.ieee.org/book/6267440 22 01 0018 Nur für Angehörige der Universität Hamburg: Volltextzugang von außerhalb des Campus http://emedien.sub.uni-hamburg.de/han/ieee/ieeexplore.ieee.org/book/6267440 23 01 0830 MIT Press EBook https://ieeexplore.ieee.org/book/6267440 100 01 3100 https://ieeexplore.ieee.org/book/6267440 100 01 3100 für Uniangehörige: Zugang weltweit http://han.med.uni-magdeburg.de/han/mitvia-ieee/ieeexplore.ieee.org/book/6267440 370 01 4370 E-Book: Zugriff im HCU-Netz. Zugriff von außerhalb nur für HCU-Angehörige möglich https://ieeexplore.ieee.org/book/6267440 2015 01 DE-93 https://ieeexplore.ieee.org/book/6267440 23 01 0830 2018-01805, 2018-01806, 2018-01808 22 01 0018 olrm-h228-MITIEEE 23 01 0830 olr-MIT 100 01 3100 OLR-MIT-CEC 370 01 4370 olr-ebook mitieee 370 01 4370 2021.12.01 |
| allfieldsGer |
9780262284448 ebook 978-0-262-28444-8 (DE-627)1727349482 (DE-599)KEP05511959X (OCoLC)857967378 (MITPRESS)6267440 (EBP)05511959X DE-627 ger DE-627 rda eng 006.3 SEPA ST 308 SEPA rvk (DE-625)rvk/143655: ST 300 SEPA rvk (DE-625)rvk/143650: ST 285 SEPA rvk (DE-625)rvk/143648: 54.72 bkl Stone, Peter 1971- verfasserin aut Layered learning in multiagent systems a winning approach to robotic soccer Peter Stone Cambridge, Massachusetts MIT Press c2000 1 PDF (xii, 272 pages) illustrations. Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Intelligent robotics and autonomous agents series Includes bibliographical references (p. [261]-272). - Description based on PDF viewed 12/23/2015 This book looks at multiagent systems that consist of teams of autonomous agents acting in real-time, noisy, collaborative, and adversarial environments. The book makes four main contributions to the fields of machine learning and multiagent systems.First, it describes an architecture within which a flexible team structure allows member agents to decompose a task into flexible roles and to switch roles while acting. Second, it presents layered learning, a general-purpose machine-learning method for complex domains in which learning a mapping directly from agents' sensors to their actuators is intractable with existing machine-learning methods. Third, the book introduces a new multiagent reinforcement learning algorithm--team-partitioned, opaque-transition reinforcement learning (TPOT-RL)--designed for domains in which agents cannot necessarily observe the state-changes caused by other agents' actions. The final contribution is a fully functioning multiagent system that incorporates learning in a real-time, noisy domain with teammates and adversaries--a computer-simulated robotic soccer team.Peter Stone's work is the basis for the CMUnited Robotic Soccer Team, which has dominated recent RoboCup competitions. RoboCup not only helps roboticists to prove their theories in a realistic situation, but has drawn considerable public and professional attention to the field of intelligent robotics. The CMUnited team won the 1999 Stockholm simulator competition, outscoring its opponents by the rather impressive cumulative score of 110-0. Mode of access: World Wide Web. Robotics Multiagent systems s (DE-588)4304075-5 (DE-627)121632806 (DE-576)211064432 Autonomer Roboter gnd s (DE-588)4389058-1 (DE-627)189373342 (DE-576)211924512 Mehragentensystem gnd (DE-627) 9780262194389 Erscheint auch als Druck-Ausgabe 9780262194389 Erscheint auch als Druck-Ausgabe Stone, Peter, 1971 - Layered learning in multiagent systems Cambridge, Mass. [u.a.] : MIT Press, 2000 XII, 272 S. (DE-627)30617314X (DE-576)08680636X 0262194384 https://ieeexplore.ieee.org/book/6267440 X:MITPRESS Verlag lizenzpflichtig ZDB-37-IEM 2012 GBV_ILN_22 ISIL_DE-18 SYSFLAG_1 GBV_KXP GBV_ILN_22_i22818 GBV_ILN_23 ISIL_DE-830 GBV_ILN_100 ISIL_DE-Ma9 GBV_ILN_370 ISIL_DE-1373 GBV_ILN_2015 ISIL_DE-93 ST 308 Robotics, CAD, CAM, CAE etc. Informatik Monografien Künstliche Intelligenz Robotics, CAD, CAM, CAE etc. (DE-627)1271505975 (DE-625)rvk/143655: (DE-576)201505975 ST 300 Allgemeines Informatik Monografien Künstliche Intelligenz Allgemeines (DE-627)1271119005 (DE-625)rvk/143650: (DE-576)201119005 ST 285 Computer supported cooperative work (CSCW), Groupware Informatik Monografien Software und -entwicklung Computer supported cooperative work (CSCW), Groupware (DE-627)1270877453 (DE-625)rvk/143648: (DE-576)200877453 54.72 Künstliche Intelligenz SEPA (DE-627)10641240X BO 045F 006.3 22 01 0018 3848475545 olrm-h228-MITIEEE zi22818 03-02-21 23 01 0830 3957241049 olr-MIT i z 23-07-21 100 01 3100 4472468158 09 --%%-- eBook MIT Press --%%-- --%%-- OLR-MIT-CEC Vervielfältigungen (z.B. Kopien, Downloads) sind nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. z 30-01-24 370 01 4370 4011222461 olr-ebook mitieee Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. i z 01-12-21 2015 01 DE-93 3740751339 00 --%%-- --%%-- p --%%-- Campuslizenz l01 18-08-20 22 01 0018 Volltextzugang Campus https://ieeexplore.ieee.org/book/6267440 22 01 0018 Nur für Angehörige der Universität Hamburg: Volltextzugang von außerhalb des Campus http://emedien.sub.uni-hamburg.de/han/ieee/ieeexplore.ieee.org/book/6267440 23 01 0830 MIT Press EBook https://ieeexplore.ieee.org/book/6267440 100 01 3100 https://ieeexplore.ieee.org/book/6267440 100 01 3100 für Uniangehörige: Zugang weltweit http://han.med.uni-magdeburg.de/han/mitvia-ieee/ieeexplore.ieee.org/book/6267440 370 01 4370 E-Book: Zugriff im HCU-Netz. Zugriff von außerhalb nur für HCU-Angehörige möglich https://ieeexplore.ieee.org/book/6267440 2015 01 DE-93 https://ieeexplore.ieee.org/book/6267440 23 01 0830 2018-01805, 2018-01806, 2018-01808 22 01 0018 olrm-h228-MITIEEE 23 01 0830 olr-MIT 100 01 3100 OLR-MIT-CEC 370 01 4370 olr-ebook mitieee 370 01 4370 2021.12.01 |
| allfieldsSound |
9780262284448 ebook 978-0-262-28444-8 (DE-627)1727349482 (DE-599)KEP05511959X (OCoLC)857967378 (MITPRESS)6267440 (EBP)05511959X DE-627 ger DE-627 rda eng 006.3 SEPA ST 308 SEPA rvk (DE-625)rvk/143655: ST 300 SEPA rvk (DE-625)rvk/143650: ST 285 SEPA rvk (DE-625)rvk/143648: 54.72 bkl Stone, Peter 1971- verfasserin aut Layered learning in multiagent systems a winning approach to robotic soccer Peter Stone Cambridge, Massachusetts MIT Press c2000 1 PDF (xii, 272 pages) illustrations. Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Intelligent robotics and autonomous agents series Includes bibliographical references (p. [261]-272). - Description based on PDF viewed 12/23/2015 This book looks at multiagent systems that consist of teams of autonomous agents acting in real-time, noisy, collaborative, and adversarial environments. The book makes four main contributions to the fields of machine learning and multiagent systems.First, it describes an architecture within which a flexible team structure allows member agents to decompose a task into flexible roles and to switch roles while acting. Second, it presents layered learning, a general-purpose machine-learning method for complex domains in which learning a mapping directly from agents' sensors to their actuators is intractable with existing machine-learning methods. Third, the book introduces a new multiagent reinforcement learning algorithm--team-partitioned, opaque-transition reinforcement learning (TPOT-RL)--designed for domains in which agents cannot necessarily observe the state-changes caused by other agents' actions. The final contribution is a fully functioning multiagent system that incorporates learning in a real-time, noisy domain with teammates and adversaries--a computer-simulated robotic soccer team.Peter Stone's work is the basis for the CMUnited Robotic Soccer Team, which has dominated recent RoboCup competitions. RoboCup not only helps roboticists to prove their theories in a realistic situation, but has drawn considerable public and professional attention to the field of intelligent robotics. The CMUnited team won the 1999 Stockholm simulator competition, outscoring its opponents by the rather impressive cumulative score of 110-0. Mode of access: World Wide Web. Robotics Multiagent systems s (DE-588)4304075-5 (DE-627)121632806 (DE-576)211064432 Autonomer Roboter gnd s (DE-588)4389058-1 (DE-627)189373342 (DE-576)211924512 Mehragentensystem gnd (DE-627) 9780262194389 Erscheint auch als Druck-Ausgabe 9780262194389 Erscheint auch als Druck-Ausgabe Stone, Peter, 1971 - Layered learning in multiagent systems Cambridge, Mass. [u.a.] : MIT Press, 2000 XII, 272 S. (DE-627)30617314X (DE-576)08680636X 0262194384 https://ieeexplore.ieee.org/book/6267440 X:MITPRESS Verlag lizenzpflichtig ZDB-37-IEM 2012 GBV_ILN_22 ISIL_DE-18 SYSFLAG_1 GBV_KXP GBV_ILN_22_i22818 GBV_ILN_23 ISIL_DE-830 GBV_ILN_100 ISIL_DE-Ma9 GBV_ILN_370 ISIL_DE-1373 GBV_ILN_2015 ISIL_DE-93 ST 308 Robotics, CAD, CAM, CAE etc. Informatik Monografien Künstliche Intelligenz Robotics, CAD, CAM, CAE etc. (DE-627)1271505975 (DE-625)rvk/143655: (DE-576)201505975 ST 300 Allgemeines Informatik Monografien Künstliche Intelligenz Allgemeines (DE-627)1271119005 (DE-625)rvk/143650: (DE-576)201119005 ST 285 Computer supported cooperative work (CSCW), Groupware Informatik Monografien Software und -entwicklung Computer supported cooperative work (CSCW), Groupware (DE-627)1270877453 (DE-625)rvk/143648: (DE-576)200877453 54.72 Künstliche Intelligenz SEPA (DE-627)10641240X BO 045F 006.3 22 01 0018 3848475545 olrm-h228-MITIEEE zi22818 03-02-21 23 01 0830 3957241049 olr-MIT i z 23-07-21 100 01 3100 4472468158 09 --%%-- eBook MIT Press --%%-- --%%-- OLR-MIT-CEC Vervielfältigungen (z.B. Kopien, Downloads) sind nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. z 30-01-24 370 01 4370 4011222461 olr-ebook mitieee Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. i z 01-12-21 2015 01 DE-93 3740751339 00 --%%-- --%%-- p --%%-- Campuslizenz l01 18-08-20 22 01 0018 Volltextzugang Campus https://ieeexplore.ieee.org/book/6267440 22 01 0018 Nur für Angehörige der Universität Hamburg: Volltextzugang von außerhalb des Campus http://emedien.sub.uni-hamburg.de/han/ieee/ieeexplore.ieee.org/book/6267440 23 01 0830 MIT Press EBook https://ieeexplore.ieee.org/book/6267440 100 01 3100 https://ieeexplore.ieee.org/book/6267440 100 01 3100 für Uniangehörige: Zugang weltweit http://han.med.uni-magdeburg.de/han/mitvia-ieee/ieeexplore.ieee.org/book/6267440 370 01 4370 E-Book: Zugriff im HCU-Netz. Zugriff von außerhalb nur für HCU-Angehörige möglich https://ieeexplore.ieee.org/book/6267440 2015 01 DE-93 https://ieeexplore.ieee.org/book/6267440 23 01 0830 2018-01805, 2018-01806, 2018-01808 22 01 0018 olrm-h228-MITIEEE 23 01 0830 olr-MIT 100 01 3100 OLR-MIT-CEC 370 01 4370 olr-ebook mitieee 370 01 4370 2021.12.01 |
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This book looks at multiagent systems that consist of teams of autonomous agents acting in real-time, noisy, collaborative, and adversarial environments. The book makes four main contributions to the fields of machine learning and multiagent systems.First, it describes an architecture within which a flexible team structure allows member agents to decompose a task into flexible roles and to switch roles while acting. Second, it presents layered learning, a general-purpose machine-learning method for complex domains in which learning a mapping directly from agents' sensors to their actuators is intractable with existing machine-learning methods. Third, the book introduces a new multiagent reinforcement learning algorithm--team-partitioned, opaque-transition reinforcement learning (TPOT-RL)--designed for domains in which agents cannot necessarily observe the state-changes caused by other agents' actions. The final contribution is a fully functioning multiagent system that incorporates learning in a real-time, noisy domain with teammates and adversaries--a computer-simulated robotic soccer team.Peter Stone's work is the basis for the CMUnited Robotic Soccer Team, which has dominated recent RoboCup competitions. RoboCup not only helps roboticists to prove their theories in a realistic situation, but has drawn considerable public and professional attention to the field of intelligent robotics. The CMUnited team won the 1999 Stockholm simulator competition, outscoring its opponents by the rather impressive cumulative score of 110-0. Includes bibliographical references (p. [261]-272). - Description based on PDF viewed 12/23/2015 |
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This book looks at multiagent systems that consist of teams of autonomous agents acting in real-time, noisy, collaborative, and adversarial environments. The book makes four main contributions to the fields of machine learning and multiagent systems.First, it describes an architecture within which a flexible team structure allows member agents to decompose a task into flexible roles and to switch roles while acting. Second, it presents layered learning, a general-purpose machine-learning method for complex domains in which learning a mapping directly from agents' sensors to their actuators is intractable with existing machine-learning methods. Third, the book introduces a new multiagent reinforcement learning algorithm--team-partitioned, opaque-transition reinforcement learning (TPOT-RL)--designed for domains in which agents cannot necessarily observe the state-changes caused by other agents' actions. The final contribution is a fully functioning multiagent system that incorporates learning in a real-time, noisy domain with teammates and adversaries--a computer-simulated robotic soccer team.Peter Stone's work is the basis for the CMUnited Robotic Soccer Team, which has dominated recent RoboCup competitions. RoboCup not only helps roboticists to prove their theories in a realistic situation, but has drawn considerable public and professional attention to the field of intelligent robotics. The CMUnited team won the 1999 Stockholm simulator competition, outscoring its opponents by the rather impressive cumulative score of 110-0. Includes bibliographical references (p. [261]-272). - Description based on PDF viewed 12/23/2015 |
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This book looks at multiagent systems that consist of teams of autonomous agents acting in real-time, noisy, collaborative, and adversarial environments. The book makes four main contributions to the fields of machine learning and multiagent systems.First, it describes an architecture within which a flexible team structure allows member agents to decompose a task into flexible roles and to switch roles while acting. Second, it presents layered learning, a general-purpose machine-learning method for complex domains in which learning a mapping directly from agents' sensors to their actuators is intractable with existing machine-learning methods. Third, the book introduces a new multiagent reinforcement learning algorithm--team-partitioned, opaque-transition reinforcement learning (TPOT-RL)--designed for domains in which agents cannot necessarily observe the state-changes caused by other agents' actions. The final contribution is a fully functioning multiagent system that incorporates learning in a real-time, noisy domain with teammates and adversaries--a computer-simulated robotic soccer team.Peter Stone's work is the basis for the CMUnited Robotic Soccer Team, which has dominated recent RoboCup competitions. RoboCup not only helps roboticists to prove their theories in a realistic situation, but has drawn considerable public and professional attention to the field of intelligent robotics. The CMUnited team won the 1999 Stockholm simulator competition, outscoring its opponents by the rather impressive cumulative score of 110-0. Includes bibliographical references (p. [261]-272). - Description based on PDF viewed 12/23/2015 |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000cam a22002652 4500</leader><controlfield tag="001">1727349482</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20220729123145.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">200818s2000 xx |||||o 00| ||eng c</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9780262284448</subfield><subfield code="c">ebook</subfield><subfield code="9">978-0-262-28444-8</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)1727349482</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)KEP05511959X</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)857967378</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(MITPRESS)6267440</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(EBP)05511959X</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">006.3</subfield><subfield code="q">SEPA</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">ST 308</subfield><subfield code="q">SEPA</subfield><subfield code="2">rvk</subfield><subfield code="0">(DE-625)rvk/143655:</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">ST 300</subfield><subfield code="q">SEPA</subfield><subfield code="2">rvk</subfield><subfield code="0">(DE-625)rvk/143650:</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">ST 285</subfield><subfield code="q">SEPA</subfield><subfield code="2">rvk</subfield><subfield code="0">(DE-625)rvk/143648:</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">54.72</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Stone, Peter</subfield><subfield code="d">1971-</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Layered learning in multiagent systems</subfield><subfield code="b">a winning approach to robotic soccer</subfield><subfield code="c">Peter Stone</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Cambridge, Massachusetts</subfield><subfield code="b">MIT Press</subfield><subfield code="c">c2000</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 PDF (xii, 272 pages)</subfield><subfield code="b">illustrations.</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="490" ind1="0" ind2=" "><subfield code="a">Intelligent robotics and autonomous agents series</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">Includes bibliographical references (p. [261]-272). - Description based on PDF viewed 12/23/2015</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">This book looks at multiagent systems that consist of teams of autonomous agents acting in real-time, noisy, collaborative, and adversarial environments. The book makes four main contributions to the fields of machine learning and multiagent systems.First, it describes an architecture within which a flexible team structure allows member agents to decompose a task into flexible roles and to switch roles while acting. Second, it presents layered learning, a general-purpose machine-learning method for complex domains in which learning a mapping directly from agents' sensors to their actuators is intractable with existing machine-learning methods. Third, the book introduces a new multiagent reinforcement learning algorithm--team-partitioned, opaque-transition reinforcement learning (TPOT-RL)--designed for domains in which agents cannot necessarily observe the state-changes caused by other agents' actions. The final contribution is a fully functioning multiagent system that incorporates learning in a real-time, noisy domain with teammates and adversaries--a computer-simulated robotic soccer team.Peter Stone's work is the basis for the CMUnited Robotic Soccer Team, which has dominated recent RoboCup competitions. RoboCup not only helps roboticists to prove their theories in a realistic situation, but has drawn considerable public and professional attention to the field of intelligent robotics. 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