MACI: Multi-Agent Collaborative Intelligence for Adaptive Reasoning and Temporal Planning

• URL: http://arxiv.org/abs/2501.16689v2
• Date: Wed, 29 Jan 2025 07:23:47 GMT
• Title: MACI: Multi-Agent Collaborative Intelligence for Adaptive Reasoning and Temporal Planning
• Authors: Edward Y. Chang,
• Abstract summary: Multi-Agent Collaborative Intelligence (MACI)<n>A framework comprising three key components: 1) a meta-planner (MP) that identifies, formulates, and refines all roles and constraints of a task while generating a dependency graph, with common-sense augmentation to ensure realistic and practical constraints; 2) a collection of agents to facilitate planning and address task-specific requirements; and 3) a run-time monitor that manages plan adjustments as needed.
• Score: 2.5200794639628032
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Artificial intelligence requires deliberate reasoning, temporal awareness, and effective constraint management, capabilities traditional LLMs often lack due to their reliance on pattern matching, limited self-verification, and inconsistent constraint handling. We introduce Multi-Agent Collaborative Intelligence (MACI), a framework comprising three key components: 1) a meta-planner (MP) that identifies, formulates, and refines all roles and constraints of a task (e.g., wedding planning) while generating a dependency graph, with common-sense augmentation to ensure realistic and practical constraints; 2) a collection of agents to facilitate planning and address task-specific requirements; and 3) a run-time monitor that manages plan adjustments as needed. By decoupling planning from validation, maintaining minimal agent context, and integrating common-sense reasoning, MACI overcomes the aforementioned limitations and demonstrates robust performance in two scheduling problems.

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