Achieving Unanimous Consensus in Decision Making Using Multi-Agents
- URL: http://arxiv.org/abs/2504.02128v1
- Date: Wed, 02 Apr 2025 21:02:54 GMT
- Title: Achieving Unanimous Consensus in Decision Making Using Multi-Agents
- Authors: Apurba Pokharel, Ram Dantu, Shakila Zaman, Sirisha Talapuru, Vinh Quach,
- Abstract summary: This paper introduces a novel deliberation-based consensus mechanism where Large Language Models (LLMs) act as rational agents engaging in structured discussions to reach a unanimous consensus.<n>By leveraging graded consensus and a multi-round deliberation process, our approach ensures both unanimous consensus for definitive problems and graded confidence for prioritized decisions and policies.<n>We also address key challenges with this novel approach such as degeneration of thoughts, hallucinations, malicious models and nodes, resource consumption, and scalability.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Blockchain consensus mechanisms have relied on algorithms such as Proof-of-Work (PoW) and Proof-of-Stake (PoS) to ensure network functionality and integrity. However, these approaches struggle with adaptability for decision-making where the opinions of each matter rather than reaching an agreement based on honest majority or weighted consensus. This paper introduces a novel deliberation-based consensus mechanism where Large Language Models (LLMs) act as rational agents engaging in structured discussions to reach a unanimous consensus. By leveraging graded consensus and a multi-round deliberation process, our approach ensures both unanimous consensus for definitive problems and graded confidence for prioritized decisions and policies. We provide a formalization of our system and use it to show that the properties of blockchains: consistency, agreement, liveness, and determinism are maintained. Moreover, experimental results demonstrate our system's feasibility, showcasing how our deliberation method's convergence, block properties, and accuracy enable decision-making on blockchain networks. We also address key challenges with this novel approach such as degeneration of thoughts, hallucinations, malicious models and nodes, resource consumption, and scalability.
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