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|a 9780128209448
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|z 9780128206768
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|a Marwala, Tshilidzi,
|d 1971-
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|a Rational machines and artificial intelligence /
|c Tshilidzi Marwala.
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|a London, United Kingdom :
|b Academic Press,
|c 2021.
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|a 1 online resource
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|a text
|b txt
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|a computer
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|a online resource
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|a Includes index.
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|a Chapter 1. Introduction to machine and human rationality -- Chapter 2. What is machine vs human rationality? -- Chapter 3. Rational machine -- Chapter 4. Felxibly bounded rationality -- Chapter 5. Rational expectation -- Chapter 6. Rational choice -- Chapter 7. Bounded rational counterfactuals -- Chapter 8. Rational opportunity cost -- Chapter 9. Can machines be rational? -- Chapter 10. Can rationality be measured? -- Chapter 11. Is machine rationality subjective? -- Chapter 12. Group vs individual rationality -- Chapter 13. Human vs machine rationality -- Chapter 14. Rational markets -- Chapter 15. Human vs machine ethics -- Chapter 16. Conclusion.
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|a "Intelligent machines are populating our social, economic and political spaces. These intelligent machines are powered by Artificial Intelligence technologies such as deep learning. They are used in decision making. One element of decision making is the issue of rationality. Regulations such as the General Data Protection Regulation (GDPR) require that decisions that are made by these intelligent machines are explainable. Rational Machines and Artificial Intelligence proposes that explainable decisions are good but the explanation must be rational to prevent these decisions from being challenged. Noted author Tshilidzi Marwala studies the concept of machine rationality and compares this to the rationality bounds prescribed by Nobel Laureate Herbert Simon and rationality bounds derived from the work of Nobel Laureates Richard Thaler and Daniel Kahneman. Rational Machines and Artificial Intelligence describes why machine rationality is flexibly bounded due to advances in technology. This effectively means that optimally designed machines are more rational than human beings. Readers will also learn whether machine rationality can be quantified and identify how this can be achieved. Furthermore, the author discusses whether machine rationality is subjective. Finally, the author examines whether a population of intelligent machines collectively make more rational decisions than individual machines. Examples in biomedical engineering, social sciences and the financial sectors are used to illustrate these concepts"--
|c Provided by publisher.
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|a Artificial intelligence.
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|a Decision making
|x Data processing.
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|a Artificial Intelligence
|0 (DNLM)D001185
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|a Intelligence artificielle.
|0 (CaQQLa)201-0008626
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|a Prise de d�ecision
|0 (CaQQLa)201-0007575
|x Informatique.
|0 (CaQQLa)201-0380011
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650 |
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|a artificial intelligence.
|2 aat
|0 (CStmoGRI)aat300251574
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|a Artificial intelligence
|2 fast
|0 (OCoLC)fst00817247
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650 |
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|a Decision making
|x Data processing
|2 fast
|0 (OCoLC)fst00889041
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|i Print version:
|z 0128206764
|z 9780128206768
|w (OCoLC)1204137242
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856 |
4 |
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|u https://sciencedirect.uam.elogim.com/science/book/9780128206768
|z Texto completo
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