📝 SummarXiv

Abstract

In many MASs, links to malicious agents cannot be severed immediately. Under these conditions, averaging-only consensus mechanisms typically lack sufficient resistance, leaving the system vulnerable to harmful deviations. To address this challenge, this brief leverages the Boomerang Effect from sociology, which drives normal agents to firmly reject malicious inputs, although this strategy may appear overly cautious. Thus, this brief emphasizes the necessity of acknowledging the resulting trade-off between cost and convergence speed in practice. To address this, the additional costs induced by Boomerang-style fusion is analyzed and a cost aware evolution rate adjustment mechanism is proposed. Multi-robot simulations demonstrate that this mechanism suppresses excess costs while maintaining resilience to extremist disruptions and ensuring stable convergence, enabling MAS to efficiently develop in a ethical order.