Controlling Uncertainty

Decision Making and Learning in Complex Worlds

Inbunden, Engelska, 2010

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Beskrivning

Controlling Uncertainty: Decision Making and Learning in Complex Worlds reviews and discusses the most current research relating to the ways we can control the uncertain world around us. Features reviews and discussions of the most current research in a number of fields relevant to controlling uncertainty, such as psychology, neuroscience, computer science and engineeringPresents a new framework that is designed to integrate a variety of disparate fields of researchRepresents the first book of its kind to provide a general overview of work related to understanding control

Produktinformation

Utgivningsdatum:2010-09-24
Mått:158 x 236 x 25 mm
Vikt:658 g
Format:Inbunden
Språk:Engelska
Antal sidor:360
Förlag:John Wiley and Sons Ltd
ISBN:9781405199469

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Mer om författaren

Magda Osman is a Lecturer in Experimental Cognitive Psychology in Queen Mary University of London. She has published in a wide range of journals on topics ranging from problem solving in abstract, social, and applied settings; motor learning; conscious and unconscious reasoning and decision making; and the cognitive basis of deception.

Recensioner i media

"The concepts are presented thoughtfully, clearly, and engagingly." (Booknews, 1 February 2011) "Osman (experimental cognitive psychology, Queen Mary U., England) brings key ideas from a variety of research disciplines together to review and examine current research on how people can control the uncertainties around them." (Reference and Research Book News, February 2011)

Innehållsförteckning

Preface: The Master Puppeteer. Acknowledgements.1. Introduction.2. Causation and Agency.3. Control Systems Engineering.4. Cybernetics, Artificial Intelligence and Machine Learning.5. Human Factors (HCI, Ergonomics and Cognitive Engineering).6. Social Psychology, Organizational Psychology and Management.7. Cognitive Psychology.8. Neuroscience.9. Synthesis.10. Epilogue: The Master Puppeteer.References.Index.