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Quantum-inspired modeling of distributed intelligence systems with artificial intelligent agents self-organization
A P Alodjants1, D V Tsarev1, A E Avdyushina1
1ITMO University, St. Petersburg, Russia, 197101.
Scientific Reports
|July 4, 2024
Summary
This study introduces a quantum-inspired model for distributed intelligence systems, enhancing user satisfaction by adapting artificial intelligence agents to natural users. It reveals how AIAs and NIAs interact, influencing opinion formation and social impact through phase transitions.
Area of Science:
- Interdisciplinary studies integrating natural and artificial intelligence.
- Complex systems and network theory.
- Quantum-inspired computational models.
Background:
- Distributed intelligence systems (DIS) leverage natural intelligence agents (NIAs) and artificial intelligence agents (AIAs) for decision-making.
- Current DIS face challenges in optimizing user satisfaction and managing information flow between agents.
- Understanding collective behavior and opinion formation in human-AI networks is crucial for digitalization.
Purpose of the Study:
- To propose a novel quantum-inspired approach for analyzing DIS composed of NIAs and AIAs.
- To investigate the role of cooperativity parameters in NIA-AIA interactions and their impact on decision-making.
- To explore opinion formation and social impact dynamics within DIS, focusing on collective emotional states.
Main Methods:
- Developed a quantum-inspired model mapping NIA cognitive states (valence-arousal) to a two-level quantum system.
- Analyzed avatar-avatar networks where avatars transmit information and users provide feedback (like/dislike).
- Introduced generalized cooperativity parameters to quantify NIA-AIA communication and information loss.
Main Results:
- Identified a second-order non-equilibrium phase transition governing opinion formation and social impact.
- Demonstrated that above the threshold (high cooperativity), stable information fields emerge, leading to adaptation.
- Showed that below the threshold (weak coupling), information diffusion is suppressed, inhibiting opinion formation but enabling AIA self-organization.
Conclusions:
- The study provides a framework for understanding collective behavior in DIS using quantum-inspired principles.
- Adaptive coupling rates between AIAs and NIAs can enhance decision-making processes and user impact.
- Findings offer new perspectives for AIAs as effective teammates in human-AI collaborative environments.
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