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Buch (Hardcover): Fachbuch
Multi-LLM Agent Collaborative Intelligence
The Path to Artificial General Intelligence, Volume 1
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Unsere-Artikel-Nr.: P36712713
EAN: 9798400731976
Erhältlich:
Nicht auf Lager
Zustellung: Di, 08.09.2026
Versand: Kostenlos
CHF 146.–
Beschreibung
Today's large language models excel at pattern recall yet falter on long-range planning, self-critique, context loss, and the tendency of maximum-likelihood training to reward popularity over quality. MACI offers a promising route to AGI by orchestrating specialized LLM agents through explicit protocols rather than enlarging a single model. Several modules remedy complementary weaknesses: adversarial-collaborative debate surfaces hidden assumptions; critical-reading rubrics filter incoherent arguments; information-theoretic signals steer dialogue quantitatively; transactional memory enables reliable long-horizon execution; and a dual-agent ethical court adjudicates outputs. Crucially, MACI also modulates linguistic behavior, tuning each agent's contentiousness and emotional tone, so the collective explores ideas from contrasting, affect-aware perspectives before converging. Fourteen aphorisms distill the framework's philosophy, including: Intelligence emerges from regulated collaboration, not isolated brilliance Exploration must remain in tension with exploitation Across healthcare diagnosis, investment support, scheduling, supply-chain management, and news-bias mitigation, MACI ensembles deliver significant improvements in reasoning depth, planning horizon, and reliability compared with similar-sized single models. By uniting structured debate, information-theoretic coordination, persistent memory, affect-aware discourse, and deliberative ethics, MACI demonstrates that rigorously validated multi-agent collaboration provides a practical, interpretable path toward robust general intelligence.
Spezifikationen
Sprache
- Englisch
Autor
- Edward Y. Chang
Erscheinungsjahr
- 2026
Format
- Buch (Hardcover)
Anzahl Seiten
- 598