HactarV2: An Agent Team Strategy Based on Implicit Coordination
In this paper we report on the design and implementation of our multi-agent system, called HactarV2, for the Agent Contest 2011. HactarV2 has been implemented in the agent programming language Goal. One of the main challenges of the Agent Contest is to design a decentralized multi-agent system that is able to strategically compete with other agent teams. To address this challenge, the strategy of HactarV2 is based on implicit coordination between agents and there is no central manager that keeps track of all information. The aim, moreover, has been to minimize the communication between agents. Communication is used by HactarV2 agents to ensure that each of them maintains the same map of the environment. The Mars scenario of this year required agents to explore, locate and occupy high valued zones on the planet Mars. Because initially agents are randomly placed on the map, in the first phase of the game the agents individually explore the map and update each other. Agents have different roles and we describe the strategies used by individual agents per role. In the second phase of the game, which starts when the agents have located high value nodes on the map, the agents group together and act as a swarm to maintain and possibly expand the zone on the map that is occupied by the agents.
KeywordsPath Planning Defensive Strategy Goal Agent Optimum Zone Agent Team
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- 1.Adams, D.: Life, the Universe and Everything. Harmony Books (1982)Google Scholar
- 2.Schwaber, K.: Scrum development process. In: Proceedings of the 10th Annual ACM Conference on Object Oriented Programming Systems, Languages, and Applications (OOPSLA), pp. 117–134 (1995)Google Scholar
- 3.iceScrum. icescrum, free and opensource platform for your agile developments (2009), http://www.icescrum.org/en/
- 5.Hindriks, K.V.: Programming rational agents in goal. In: Multi-Agent Programming: Languages, Tools and Applications, pp. 119–157. Springer, US (2009)Google Scholar
- 7.(2011), http://mmi.tudelft.nl/trac/goal
- 8.Behrens, T., Hindriks, K., Dix, J.: Towards an environment interface standard for agent platforms. Annals of Mathematics and Artificial Intelligence, 1–35 (2010)Google Scholar
- 9.Barker, C.: LPA Win-Prolog goodies. A WWW collection of Prolog source snippets (1999), http://colin.barker.pagesperso-orange.fr/lpa/dijkstra.htm