GenCOA generates a diverse pool of multi-agent mission plans by splitting task allocation (genetic algorithm) from task sequencing (graph reinforcement learning), reaching about 96% of the optimal completion rate.
A multi-agent architecture for modelling and simulation of small military unit combat in asymmetric warfare,
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Automated Generation of Diverse Courses of Actions for Multi-Agent Operations using Binary Optimization and Graph Learning
GenCOA generates a diverse pool of multi-agent mission plans by splitting task allocation (genetic algorithm) from task sequencing (graph reinforcement learning), reaching about 96% of the optimal completion rate.