Computational Collective IntelligenceIntroducing 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. |
Contents
IntelligenceOur Present State of Understanding | 11 |
Problems when a Social Structure Grows | 131 |
66 | 157 |
Copyright | |
8 other sections not shown
Common terms and phrases
abilities Abstract Machine Adleman's agents algorithm analog computers analyze ants approach architecture artificial intelligence assumed backtrack bacteria basic behavior Brownian clause collective intelligence communication complexity computational process computational space concept configuration considered cooperation create defined definition of collective denoted deterministic Deterministic Turing Machine digital computers discussed displacements DNA computer elements emerge environment evaluation example execution exists Expert System fact factors formal function given in Figure goals hardware Horn clauses human implemented individual intelligence inference process information molecules input interaction language let us look logical mathematical membrane model of computations multiset NDTM necessary nondeterministic Nondeterministic Turing Machine operations organization parallel point of view possible predicate present problem PROLOG program quasi-chaotic Random PROLOG Processor rendezvous result retract rules Section simulation social structure solution solve specific tasks Turing Machine unification variables Warren Abstract Machine
References to this book
Intelligent Cities and Globalisation of Innovation Networks Nicos Komninos No preview available - 2008 |