multi-agent-architecture-aa570311·1 events·first seen Aliases: multi-agent architecture
The paper introduces MA²P, a multi-agent framework designed for complex persuasion tasks where the persuadee's internal states are latent. The system coordinates perception management, mental-state inference, strategy execution, memory, and evaluation modules, and adds a meta-cognitive configurator that selects domain-appropriate strategies from a structured knowledge base to reduce cross-domain performance variance. Experiments show higher persuasion success rates compared to baselines. The work addresses a known weakness of LLMs in producing generic or weakly grounded persuasive responses.