A new multi-agent cooperative path planning based on the Crow Search Algorithm
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Date
2024
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Abstract :
The limitations of traditional optimization techniques in addressing complex
problems within multi-agent systems (MAS) necessitate the exploration of
innovative approaches.This work delves into the potential of metaheuristics, a
family of algorithms inspired by natural processes. We specifically investigate the
Crow Search Algorithm (CSA) and Particle Swarm Optimization (PSO) as promising
tools for MAS path planning. By incorporating the exploration-exploitation
balance inherent to these metaheuristics, we aim to develop robust and
adaptable path planning strategies that empower agents within MAS to navigate
complex environments effectively.