This volume presents for the first time a complete theory of collective intelligence, helping to explain this growing area of non-deterministic computing. The author brings together ideas from different areas, making this a useful resource not only for computer scientists, but also for researchers working on problems in machine learning and artificial intelligence. Random PROLOG Processor (RPP) is used to illustrate the theory.
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"Develops a formal definition of collective intelligence (CI) and practical guidelines for its assessment and applications." (SciTech Book News Vol. 25, No. 2 June 2001)
From the Back Cover
Introducing a groundbreaking approach to understanding, measuring, and applying Collective Intelligence
Does Collective Intelligence (CI) exist and, if so, how can it be characterized, quantified, and harnessed? Questions such as these continue to be hotly debated within both the scientific and philosophical communities. Yet few researchers working in the fields of artificial intelligence or distributed computing doubt CI's enormous potential value to the future of computing. Unfortunately, for lack of a rigorous, formal theory of Collective Intelligence, most attempts to analyze CI systems have been disappointing, at best. In Computational Collective Intelligence, Professor Tadeusz Szuba does much to rectify that situation by developing, for the first time, both a formal definition of CI and practical guidelines for its assessment and applications.
Working from the ground up, Dr. Szuba begins with a stimulating and insightful discussion of the types of intelligence-including individual, artificial, and collective-into which he brings ideas from AI, information theory, and distributed computing, as well as psychology, sociology, animal behavior, cognitive science, and other relevant disciplines. He tackles the problem of computational models for simulating and measuring CI. He explores all theoretically feasible models of CI computations and presents a groundbreaking, nondeterministic approach using the Random PROLOG Processor (RPP) as a CI modeling and evaluation tool. He then introduces the Collective Intelligence Quotient (IQS) and develops clear-cut guidelines for measuring it. In the final chapters, he lays the foundation for a dynamic new discipline, Collective Intelligence Engineering (CIE), and considers its potential applications as an organizational restructuring tool.
Does Collective Intelligence (CI) exist and, if so, how can it be characterized, quantified, and harnessed? Questions such as these continue to be hotly debated within both the scientific and philosophical communities. Yet few researchers working in the fields of artificial intelligence or distributed computing doubt CI's enormous potential value to the future of computing. Unfortunately, for lack of a rigorous, formal theory of Collective Intelligence, most attempts to analyze CI systems have been disappointing, at best. In Computational Collective Intelligence, Professor Tadeusz Szuba does much to rectify that situation by developing, for the first time, both a formal definition of CI and practical guidelines for its assessment and applications.
Working from the ground up, Dr. Szuba begins with a stimulating and insightful discussion of the types of intelligence-including individual, artificial, and collective-into which he brings ideas from AI, information theory, and distributed computing, as well as psychology, sociology, animal behavior, cognitive science, and other relevant disciplines. He tackles the problem of computational models for simulating and measuring CI. He explores all theoretically feasible models of CI computations and presents a groundbreaking, nondeterministic approach using the Random PROLOG Processor (RPP) as a CI modeling and evaluation tool. He then introduces the Collective Intelligence Quotient (IQS) and develops clear-cut guidelines for measuring it. In the final chapters, he lays the foundation for a dynamic new discipline, Collective Intelligence Engineering (CIE), and considers its potential applications as an organizational restructuring tool.
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