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on1393300641 |
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OCoLC |
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20241006213017.0 |
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m o d |
| 007 |
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230813s2023 sz o 101 0 eng d |
| 040 |
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|a YDX
|b eng
|c YDX
|d GW5XE
|d EBLCP
|d OCLCQ
|d OCLCO
|d YDX
|d WSU
|d OCLCO
|d UKAHL
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| 020 |
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|a 9783031387128
|q (electronic bk.)
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| 020 |
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|a 3031387120
|q (electronic bk.)
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| 020 |
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|z 3031387112
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| 020 |
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|z 9783031387111
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| 024 |
7 |
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|a 10.1007/978-3-031-38712-8
|2 doi
|
| 035 |
|
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|a (OCoLC)1393300641
|
| 050 |
|
4 |
|a QA76.76.I58
|b M85 2022
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| 049 |
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|a HCDD
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| 111 |
2 |
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|a Multi-Agent Programming Contest
|n (16th :
|d 2022)
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| 245 |
1 |
4 |
|a The Multi-Agent Programming Contest 2022
|h [electronic resource] :
|b coordinating agents in a dynamic world : agents follow the rules, or not /
|c Tobias Ahlbrecht, Jürgen Dix, Niklas Fiekas, Tabajara Krausburg, editors.
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| 246 |
3 |
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|a MAPC 2022
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| 260 |
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|a Cham, Switzerland :
|b Springer,
|c 2023.
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| 300 |
|
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|a 1 online resource
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| 490 |
1 |
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|a Lecture notes in computer science ;
|v 13997
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| 490 |
1 |
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|a Lecture notes in artificial intelligence
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| 490 |
1 |
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|a LNCS sublibrary, SL 7, Artificial intelligence
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| 500 |
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|a Includes author index.
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| 520 |
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|a This book constitutes the 16th edition of the annual Multi-Agent Programming Contest, MAPC 2022. It gives an overview of the competition, describes the current scenario. The first paper describes the contest in general and this edition in particular, focusing on the organizers observations. The following papers are written by the participants of the contest, describing their team of agents and its performance in more detail.
|
| 505 |
0 |
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|a The MAPC 2022 - Background, realization & outcomes -- The Multi-Agent Programming Contest 2022 -- Optimization-based Agents in the 16th Multi-Agent Programming Contest -- The contestants and their agents -- MMD: The Block Building Agent Team with Explainable Intentions -- GOALdigger-AIG-Hagen Multi-Agent System: Team Description -- General deSouches commands multi-agent army for performing in Agents Assemble III scenario: FIT-BUT at MAPC 2022 -- The 16th Edition of the Multi-Agent Programming Contest - The GOAL-DTU Team -- LI(A)RA Team - A Declarative and Distributed Implementation for the MAPC 2022.
|
| 650 |
|
0 |
|a Multiagent systems
|x Competitions.
|
| 655 |
|
7 |
|a proceedings (reports)
|2 aat
|
| 655 |
|
7 |
|a Conference papers and proceedings.
|2 lcgft
|
| 655 |
|
7 |
|a Actes de congrès.
|2 rvmgf
|
| 700 |
1 |
|
|a Ahlbrecht, Tobias,
|e editor.
|
| 700 |
1 |
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|a Dix, Jürgen,
|e editor.
|
| 700 |
1 |
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|a Fiekas, Niklas,
|e editor.
|
| 700 |
1 |
|
|a Krausburg, Tabajara,
|e editor.
|
| 776 |
0 |
8 |
|i Print version:
|z 3031387112
|z 9783031387111
|w (OCoLC)1384414535
|
| 830 |
|
0 |
|a Lecture notes in computer science.
|p Lecture notes in artificial intelligence.
|
| 830 |
|
0 |
|a Lecture notes in computer science ;
|v 13997.
|
| 830 |
|
0 |
|a LNCS sublibrary.
|n SL 7,
|p Artificial intelligence.
|
| 856 |
4 |
0 |
|u https://holycross.idm.oclc.org/login?auth=cas&url=https://link.springer.com/10.1007/978-3-031-38712-8
|y Click for online access
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| 903 |
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|a SPRING-ALL2023
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| 994 |
|
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|a 92
|b HCD
|