Ant-based load balancing in telecommunications networks
Adaptive Behavior
Multiagent systems: a modern approach to distributed artificial intelligence
Multiagent systems: a modern approach to distributed artificial intelligence
Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
The Cost of Application-Level Broadcast in a Fully Decentralized Peer-to-Peer Network
ISCC '02 Proceedings of the Seventh International Symposium on Computers and Communications (ISCC'02)
Performance of digital pheromones for swarming vehicle control
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
AntNet: distributed stigmergetic control for communications networks
Journal of Artificial Intelligence Research
Improving peer-to-peer resource discovery using mobile agent based referrals
AP2PC'03 Proceedings of the Second international conference on Agents and Peer-to-Peer Computing
Market-Based Distributed Task Selection in Multi-agent Swarms
IAT '06 Proceedings of the IEEE/WIC/ACM international conference on Intelligent Agent Technology
Auction-based multi-robot task allocation in COMSTAR
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Dynamic Pricing Algorithms for Task Allocation in Multi-agent Swarms
Massively Multi-Agent Technology
Distributed task selection in multi-agent based swarms using heuristic strategies
SAB'06 Proceedings of the 2nd international conference on Swarm robotics
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We address the problem of automatic target recognition (ATR) using a multi-agent swarm of unmanned aerial vehicles(UAVs) deployed within a reconnaissance area. Traditionally, ATR is performed by UAVs that fly within the reconnaissance area to collect image data through sensors and upload the data to a central base station for analyzing and identifying potential targets. The centralized approach to ATR introduces several problems including scalability with the number of UAVs, network delays in communicating with the central location, and, susceptibility of the system to malicious attacks on the central location. In this paper, we describe a multi-agent system of UAVs to perform ATR. We assume that each UAV has limited computational capabilities and target identification can be performed by several UAVs that combine their resources including their computational capabilities. The UAVs employ a swarming algorithm implemented through software agents to congregate at and identify potential targets, and, a gossiping mechanism to disseminate information within the swarm.