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Springer Foundations of Computational Intelligence Volume 2 - Approximate Reasoning

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Description

Foundations of Computational Intelligence Volume 2 explores the theoretical foundations and practical applications of approximate reasoning, the computational modelling of how humans reason about natural phenomena and solve real-world problems. This volume covers fuzzy sets, Dempster-Shafer theory, multi-valued logic, probability, random sets, rough sets, and near sets, alongside hybrid intelligent systems. The book combines research articles with expository papers that bridge theory and practice, offering comprehensive coverage of approximate reasoning methodologies used across computational intelligence applications. Published by Springer as part of the Studies in Computational Intelligence series (volume 202), this text serves as a resource for researchers, academics, and practitioners seeking to understand the mathematical frameworks underlying human-like reasoning in artificial systems.

Key Features

Covers fuzzy sets, Dempster-Shafer theory, and multi-valued logic for modelling various types of uncertainties.

Explores probability, random sets, and rough sets as foundational concepts in approximate reasoning.

Includes both theoretical research articles and expository papers bridging theory with real-world applications.

Part of the Studies in Computational Intelligence series, volume 202, published by Springer.

Addresses computational modelling of human reasoning processes for solving practical problems.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
15 June 2009
Listed Since
31 March 2009

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