In this paper, we describe the strategies used by our team, MLFC, that led us to achieve the 2nd place in the 15th edition of the Multi-Agent Programming Contest. The scenario used in the contest is an extension of the previous edition (14th ) “Agents Assemble” wherein two teams of agents move around a 2D grid and compete to assemble complex block structures. We discuss the languages and tools used during the development of our team. Then, we summarise the main strategies that were carried over from our previous participation in the 14th edition and list the limitations (if any) of using these strategies in the latest contest edition. We also developed new strategies that were made specifically for the extended scenario: cartography (determining the size of the map); formal verification of the map merging protocol (to provide assurances that it works when increasing the number of agents); plan cache (efficiently scaling the number of planners); task achievement (forming groups of agents to achieve tasks); and bullies (agents that focus on stopping agents from the opposing team). Finally, we give a brief overview of our performance in the contest and discuss what we believe were our shortcomings.

MLFC: From 10 to 50 Planners in the Multi-Agent Programming Contest / Cardoso, R. C.; Ferrando, A.; Papacchini, F.; Luckcuck, M.; Linker, S.; Payne, T. R.. - 12947:(2021), pp. 82-107. ( 15th Annual Multi-Agent Programming Contest, MAPC 2021 na 2021) [10.1007/978-3-030-88549-6_4].

MLFC: From 10 to 50 Planners in the Multi-Agent Programming Contest

Ferrando A.;
2021

Abstract

In this paper, we describe the strategies used by our team, MLFC, that led us to achieve the 2nd place in the 15th edition of the Multi-Agent Programming Contest. The scenario used in the contest is an extension of the previous edition (14th ) “Agents Assemble” wherein two teams of agents move around a 2D grid and compete to assemble complex block structures. We discuss the languages and tools used during the development of our team. Then, we summarise the main strategies that were carried over from our previous participation in the 14th edition and list the limitations (if any) of using these strategies in the latest contest edition. We also developed new strategies that were made specifically for the extended scenario: cartography (determining the size of the map); formal verification of the map merging protocol (to provide assurances that it works when increasing the number of agents); plan cache (efficiently scaling the number of planners); task achievement (forming groups of agents to achieve tasks); and bullies (agents that focus on stopping agents from the opposing team). Finally, we give a brief overview of our performance in the contest and discuss what we believe were our shortcomings.
2021
Inglese
15th Annual Multi-Agent Programming Contest, MAPC 2021
na
2021
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
12947
82
107
26
9783030885489
Springer Science and Business Media Deutschland GmbH
Agents Assemble; Automated Planning; JaCaMo; Multi-Agent Programming Contest; Multi-Agent Systems
Cardoso, R. C.; Ferrando, A.; Papacchini, F.; Luckcuck, M.; Linker, S.; Payne, T. R.
Atti di CONVEGNO::Relazione in Atti di Convegno
273
6
MLFC: From 10 to 50 Planners in the Multi-Agent Programming Contest / Cardoso, R. C.; Ferrando, A.; Papacchini, F.; Luckcuck, M.; Linker, S.; Payne, T. R.. - 12947:(2021), pp. 82-107. ( 15th Annual Multi-Agent Programming Contest, MAPC 2021 na 2021) [10.1007/978-3-030-88549-6_4].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1331862
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