Artificial Intelligence Techniques for Rational Decision Making

Nonfiction, Computers, Advanced Computing, Artificial Intelligence, Science & Nature, Mathematics, Statistics, General Computing
Cover of the book Artificial Intelligence Techniques for Rational Decision Making by Tshilidzi Marwala, Springer International Publishing
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: Tshilidzi Marwala ISBN: 9783319114248
Publisher: Springer International Publishing Publication: October 20, 2014
Imprint: Springer Language: English
Author: Tshilidzi Marwala
ISBN: 9783319114248
Publisher: Springer International Publishing
Publication: October 20, 2014
Imprint: Springer
Language: English

Develops insights into solving complex problems in engineering, biomedical sciences, social science and economics based on artificial intelligence. Some of the problems studied are in interstate conflict, credit scoring, breast cancer diagnosis, condition monitoring, wine testing, image processing and optical character recognition. The author discusses and applies the concept of flexibly-bounded rationality which prescribes that the bounds in Nobel Laureate Herbert Simon’s bounded rationality theory are flexible due to advanced signal processing techniques, Moore’s Law and artificial intelligence.

Artificial Intelligence Techniques for Rational Decision Making examines anddefines the concepts of causal and correlation machines and applies the transmission theory of causality as a defining factor that distinguishes causality from correlation. It develops the theory of rational counterfactuals which are defined as counterfactuals that are intended to maximize the attainment of a particular goal within the context of a bounded rational decision making process. Furthermore, it studies four methods for dealing with irrelevant information in decision making:

  • Theory of the marginalization of irrelevant information
  • Principal component analysis
  • Independent component analysis
  • Automatic relevance determination method

In addition it studies the concept of group decision making and various ways of effecting group decision making within the context of artificial intelligence.

Rich in methods of artificial intelligence including rough sets, neural networks, support vector machines, genetic algorithms, particle swarm optimization, simulated annealing, incremental learning and fuzzy networks, this book will be welcomed by researchers and students working in these areas.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

Develops insights into solving complex problems in engineering, biomedical sciences, social science and economics based on artificial intelligence. Some of the problems studied are in interstate conflict, credit scoring, breast cancer diagnosis, condition monitoring, wine testing, image processing and optical character recognition. The author discusses and applies the concept of flexibly-bounded rationality which prescribes that the bounds in Nobel Laureate Herbert Simon’s bounded rationality theory are flexible due to advanced signal processing techniques, Moore’s Law and artificial intelligence.

Artificial Intelligence Techniques for Rational Decision Making examines anddefines the concepts of causal and correlation machines and applies the transmission theory of causality as a defining factor that distinguishes causality from correlation. It develops the theory of rational counterfactuals which are defined as counterfactuals that are intended to maximize the attainment of a particular goal within the context of a bounded rational decision making process. Furthermore, it studies four methods for dealing with irrelevant information in decision making:

In addition it studies the concept of group decision making and various ways of effecting group decision making within the context of artificial intelligence.

Rich in methods of artificial intelligence including rough sets, neural networks, support vector machines, genetic algorithms, particle swarm optimization, simulated annealing, incremental learning and fuzzy networks, this book will be welcomed by researchers and students working in these areas.

More books from Springer International Publishing

Cover of the book Female Bodies and Sexuality in Iran and the Search for Defiance by Tshilidzi Marwala
Cover of the book Acoustic Emission by Tshilidzi Marwala
Cover of the book Histone Recognition by Tshilidzi Marwala
Cover of the book Psychology of Perception by Tshilidzi Marwala
Cover of the book Peacebuilding and the Rights of Indigenous Peoples by Tshilidzi Marwala
Cover of the book Essential Methods for Planning Practitioners by Tshilidzi Marwala
Cover of the book Knowledge-Driven Developments in the Bioeconomy by Tshilidzi Marwala
Cover of the book Testbeds and Research Infrastructures for the Development of Networks and Communities by Tshilidzi Marwala
Cover of the book Richard Ned Lebow: Key Texts in Political Psychology and International Relations Theory by Tshilidzi Marwala
Cover of the book International Politics and Inner Worlds by Tshilidzi Marwala
Cover of the book Machine Learning for Health Informatics by Tshilidzi Marwala
Cover of the book A Finite Element Primer for Beginners by Tshilidzi Marwala
Cover of the book Construction Program Management – Decision Making and Optimization Techniques by Tshilidzi Marwala
Cover of the book Gastrointestinal Motility Disorders by Tshilidzi Marwala
Cover of the book Projective Geometry by Tshilidzi Marwala
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy