Modeling Layered Consciousness with Multi-Agent Large Language Models

ACL ARR 2025 May Submission1420 Authors

Abstract: We propose a multi-agent framework for modeling artificial consciousness in large language models (LLMs), grounded in psychoanalytic theory. Our Psychodynamic Model simulates self-awareness, preconsciousness, and unconsciousness through agent interaction, guided by a Personality 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 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.

Paper Type: Long

Research Area: Language Modeling

Research Area Keywords: LLM/AI agents; fine-tuning; prompting

Languages Studied: English

Submission Number: 1420