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arXiv · 2510.17844

Modeling Layered Consciousness with Multi-Agent Large Language Models

Sang Hun Kim·Jongmin Lee·Dongkyu Park·So Young Lee·Yosep Chong
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Abstract

We propose a multi-agent framework for modeling artificial consciousness in large language models (LLMs), grounded in psychoanalytic theory. Our \textbf{Psychodynamic Model} simulates self-awareness, preconsciousness, and unconsciousness through agent interaction, guided by a Personalization Module combining fixed traits and dynamic needs. Using parameter-efficient fine-tuning on emotionally rich dialogues, the system was evaluated across eight personalized conditions. An LLM as a judge approach showed a 71.2\% preference for the fine-tuned model, with improved emotional depth and reduced output variance, demonstrating its potential for adaptive, personalized cognition.

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Sang Hun Kim, Jongmin Lee, Dongkyu Park, So Young Lee, Yosep Chong. 2025-10-10. Modeling Layered Consciousness with Multi-Agent Large Language Models. https://arxiv.org/abs/2510.17844

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