A framework and analysis for cooperative search using UAV swarms
Proceedings of the 2004 ACM symposium on Applied computing
MASON: A Multiagent Simulation Environment
Simulation
Demonstrating the validity of a wildfire DDDAS
ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part III
Distributed localization and mapping with a robotic swarm
SAB'04 Proceedings of the 2004 international conference on Swarm Robotics
IEEE Computational Intelligence Magazine
Agent-based simulation for UAV swarm mission planning and execution
Proceedings of the Agent-Directed Simulation Symposium
Multi-hop communications in a swarm of UAVs
Proceedings of the Agent-Directed Simulation Symposium
Design and evaluation of UAV swarm command and control strategies
Proceedings of the Agent-Directed Simulation Symposium
International Journal of Agent Technologies and Systems
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Swarm intelligent systems are simple but robust, capable of solving complex problems that no single agent could attempt. While technological advancements have driven development of multi-agent systems across disciplines, emergent behavior inherent to swarms is a desirable yet difficult property to exploit. Solutions utilizing swarm behavior have been proposed for the Cooperative Cleaning Problem, which is applicable to UAVs cooperatively searching for evasive targets. This work proposes a new agent behavior capable of partitioning a search area, and when combined with previous swarm solutions, forms an optimization problem of how to best assign swarms to a complex topology. Agent-based simulations are developed to test swarm solutions.