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.
Learning scalable policies over graphs for multi-robot task allocation using capsule attention net- works,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.LG 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
background 1representative citing papers
citing papers explorer
-
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.