Artículo: AMZ-B0FZTM1T9P
Multi-LLM Agent Collaborative Intelligence: The Path to Artificial General Intelligence
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1.41 kg
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Amazon
- UCCT (theoretical foundation). Treats LLMs as unconscious pattern repositories and defines anchoring strength as the driver of phase transitions from System-1 pattern completion to System-2 deliberation.
- SocraSynth and EVINCE (debate modulation and evidence flow). Tune contentiousness to balance exploration and convergence, and use Bayesian and information-theoretic control so that evidence is exchanged at the right time by the right roles, raising anchoring strength rather than generating noise.
- Linguistic behavior shaping. Model and regulate traits such as contentiousness, empathy, and diplomacy so agents adopt role-appropriate stances that improve critique, calibration, and consensus.
- Socratic reasoning. Use structured questioning and iterative dialogue to surface assumptions, decompose tasks, and stress-test hypotheses, turning raw pattern completion into disciplined inquiry.
- Checks-and-balances governance. Assign distinct institutional roles to agents for knowledge generation, ethical oversight (Dike), and contextual interpretation (Eris), creating accountable workflows with auditing and verifiability.
- Persistent memory and planning. Use SagaLLM for transaction-based memory with validation and rollback to maintain coherence across long workflows, and integrate ALAS for disruption-aware, multi-threaded reactive planning in realistic settings.
- Precision RAG. With SocraSynth, CRIT, and UCCT, retrieval is guided and testable. Added context increases the density of task-relevant patterns, which improves inference and reasoning.
- Polynthesis. Discover novel knowledge through polydisciplinary synthesis.
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