Multi llm agent collaborative intelligence path di chang edward (12 risultati)

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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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' and '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.…

Buch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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 exploitationAcross 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.…

Taschenbuch. Condizione: Neu. Multi-LLM Agent Collaborative Intelligence | The Path to Artificial General Intelligence, Volume 1 | Edward Y. Chang | Taschenbuch | ACM Books | Einband - flex.(Paperback) | Englisch | 2025 | Association for Computing Machinery | EAN 9798400731785 | Verantwortliche Person für die EU: Mare Nostrum Group B.V., Doelen 72, 4831 GR BREDA, NIEDERLANDE, gpsr[at]mare-nostrum[dot]co[dot]uk | Anbieter: preigu Print on Demand.…

Buch. Condizione: Neu. Multi-LLM Agent Collaborative Intelligence | The Path to Artificial General Intelligence, Volume 1 | Edward Y. Chang | Buch | ACM Books | Einband - fest (Hardcover) | Englisch | 2026 | Association for Computing Machinery | EAN 9798400731976 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. …