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Record Nr. |
UNISA996466211703316 |
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Titolo |
The Multi-Agent Programming Contest 2018 [[electronic resource] ] : Agents Teaming Up in an Urban Environment / / edited by Tobias Ahlbrecht, Jürgen Dix, Niklas Fiekas |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
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ISBN |
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Edizione |
[1st ed. 2019.] |
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Descrizione fisica |
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1 online resource (VII, 145 p. 31 illus., 21 illus. in color.) |
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Collana |
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Lecture Notes in Artificial Intelligence ; ; 11957 |
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Disciplina |
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Soggetti |
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Artificial intelligence |
Computer communication systems |
Special purpose computers |
Application software |
Coding theory |
Information theory |
Software engineering |
Artificial Intelligence |
Computer Communication Networks |
Special Purpose and Application-Based Systems |
Information Systems Applications (incl. Internet) |
Coding and Information Theory |
Software Engineering/Programming and Operating Systems |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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The Contest -- The Multi-Agent Programming Contest 2018 - A third time in the city -- The Teams -- task-oriented architecture with priority queue for BDI agents applied to the Multi Agent Programming Contest scenario -- Multi-Agent Programming Contest 2018 - The Jason-DTU Team -- SMART-JaCaMo: an Organisation-Based Team for the Multi-Agent Programming Contest -- Distributed Decision-Making based on Shared Knowledge in the Multi-Agent Programming Contest -- ROS Hybrid Behaviour Planner: Behaviour Hierarchies and Self- |
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Organisation in the Multi-Agent Programming Contest. |
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Sommario/riassunto |
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This book constitutes the 13th edition of the annual Multi-Agent Programming Contest, MAPC 2018, and presents its participants. The 2018 scenario and all its changes from previous competitions are described in the first contribution, together with a brief description and analysis of the five participating teams and a closer look at the matches. It is followed by a contribution from each team, introducing their methods and tools used to create their agent team and analyzing their performance and the contest. |
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