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Artificial Intelligence and Economic Theory: Skynet in the Market

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ISBN-13:
9783319661032
Einband:
Book
Erscheinungsdatum:
01.10.2017
Seiten:
204
Autor:
Tshilidzi Marwala
Gewicht:
484 g
Format:
244x159x20 mm
Serie:
Advanced Information and Knowledge Processing
Sprache:
Englisch
Beschreibung:

Reviews how Nobel Prize winning economic ideas are revolutionized by artificial intelligence
Introduction to Man and Machines.- Supply and Demand.- Rational Choice and Rational Expectations.- Bounded Rationality.- Behavioral Economics.- Information Asymmetry.- Game Theory.- Pricing.- Efficient Market Hypothesis.- Mechanism Design.- Portfolio Theory.- Counterfactuals.- Financial Engineering.- Causality.- Future Work.- Appendices.- Index.
This book theoretically and practically updates major economic ideas such as demand and supply, rational choice and expectations, bounded rationality, behavioral economics, information asymmetry, pricing, efficient market hypothesis, game theory, mechanism design, portfolio theory, causality and financial engineering in the age of significant advances in man-machine systems. The advent of artificial intelligence has changed many disciplines such as engineering, social science and economics. Artificial intelligence is a computational technique which is inspired by natural intelligence concepts such as the swarming of birds, the working of the brain and the pathfinding of the ants. Artificial Intelligence and Economic Theory: Skynet in the Market analyses the impact of artificial intelligence on economic theories, a subject that has not been studied. It also introduces new economic theories and these are rational counterfactuals and rational opportunity costs. These ideas are applied to diverse areas such as modelling of the stock market, credit scoring, HIV and interstate conflict. Artificial intelligence ideas used in this book include neural networks, particle swarm optimization, simulated annealing, fuzzy logic and genetic algorithms. It, furthermore, explores ideas in causality including Granger as well as the Pearl causality models.

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