Authors:
Amr Hussein
;
Carmen Gervet
and
Slim Abdennadher
Affiliation:
German University in Cairo, Egypt
Keyword(s):
Multi-agent planning, Clustering, RoboCup, Rescue, RoboCup rescue simulation.
Related
Ontology
Subjects/Areas/Topics:
Agents
;
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Cooperation and Coordination
;
Distributed and Mobile Software Systems
;
Enterprise Information Systems
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Multi-Agent Systems
;
Software Engineering
;
Symbolic Systems
;
Task Planning and Execution
Abstract:
The RoboCup Rescue Simulation system provides a rich environment for developing novel techniques for multi-agent systems. The simulation provides a city map modeled as buildings and roads with civilians amongst them. A disaster scenario is simulated causing buildings to catch fire, roads to get blocked, and civilians to get injured and/or buried. The main goal is to use the available emergency services (rescue agents) to extinguish the fires, clear the roads, and rescue the civilians. This paper describes a new multi-agent planning approach applied to the RoboCup Rescue problem. The key novelty lies in the distributed approach for task allocation and coordination. It is done through clustering the map into several overlapping maps each with a different group of agents assigned to it. Our results showed that not only we could compete against the top teams in the 2011 RoboCup Rescue Agent Simulation Competition, but we ranked 3rd in this first participation of the GUC in the competition.