Artificial Intelligence - Special issue on Robocop: the first step
Situation Based Strategic Positioning for Coordinating a Team of Homogeneous Agents
Balancing Reactivity and Social Deliberation in Multi-Agent Systems, From RoboCup to Real-World Applications (selected papers from the ECAI 2000 Workshop and additional contributions)
Layered learning in multiagent systems
Layered learning in multiagent systems
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In this paper we propose a model for coordinating teams of computational agents. This model is especially aimed for coordinating agents performing in a simulated environment of forest firefighting, although it may be used in other domains. We will start by introducing the Pyrosim platform where we are carrying out our experiments. Pyrosim is a tool developed in our laboratory that simulates a forest fire environment where software agents act under the role of firefighters that have to cooperate in order to control the fire. We will proceed by presenting a model for team coordination. With this model it is possible to define firefighting tactics that originate different team approaches to the fire. These tactics are conducted by a single agent (the Leader) that communicates high level tasks to the other agents. Agents have local autonomy and are able of cooperating locally for carrying out their tasks without using communication. Finally, we will present some results of our experiments using the proposed coordination model in two different scenarios. We will use these results to address the problem of automatic tactic selection where we are currently working on.