The Multi-Agent Programming Contest 2018 Agents Teaming Up in an Urban Environment /

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 partici...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Άλλοι συγγραφείς: Ahlbrecht, Tobias (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Dix, Jürgen (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Fiekas, Niklas (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2019.
Έκδοση:1st ed. 2019.
Σειρά:Lecture Notes in Artificial Intelligence ; 11957
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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490 1 |a Lecture Notes in Artificial Intelligence ;  |v 11957 
505 0 |a 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-Organisation in the Multi-Agent Programming Contest. 
520 |a 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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