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Agents can traverse complex maze environments more efficiently by leveraging local communication and leader-follower dynamics, achieving optimal performance with fewer resources.
More agents aren't always better: splitting resources too thinly can actually hurt multi-agent system performance, especially when individual agent failure rates increase.
Humans care more about the "personality" of robot swarms (warmth and competence) than how well they perform tasks.