How to mitigate malicious agents' impact on opinion evolution cost in MAS?
OPINION DYNAMIC UNDER MALICIOUS AGENT INFLUENCE IN MULTI-AGENT SYSTEMS: FROM THE PERSPECTIVE OF OPINION EVOLUTION COST
This paper studies how "bad actors" (malicious agents) can disrupt the "conversation" (opinion dynamics) in a multi-agent system, especially when they are the majority, by introducing extra "communication overhead" (opinion evolution cost). It proposes a solution that helps "good actors" (normal agents) identify and ignore these bad actors based on how their "talking points" (opinions) evolve, similar to detecting and filtering spam. Additionally, it proposes a mechanism to adjust the "pace of the conversation" (opinion evolution rate) to save effort in the early stages when dealing with bad actors and speed things up once they are isolated. This dynamic adjustment is key for optimizing both cost and speed, especially important for LLM-based agents where communication can be expensive. The focus on majority malicious agents and dynamic adjustment of communication based on trust makes this research particularly relevant to LLM-based multi-agent systems development.