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Artificial intelligence : a modern approach
Adapation autorisée de la 4e édition du même titre parue aux États-unis, ISBN 978-0-13-461099-3, Pearson education (C 2021)The long-anticipated revision of Artificial Intelligence: A Modern Approach explores the full breadth and depth of the field of artificial intelligence (AI). The 4th Edition bri...
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| Auteurs principaux : | , |
|---|---|
| Format : | Livre |
| Langue : | anglais |
| Titre complet : | Artificial intelligence : a modern approach / Stuart J. Russell and Peter Norvig |
| Édition : | Fourth edition, global edition |
| Publié : |
Harlow :
Pearson education limited
, C 2022 |
| Description matérielle : | 1 vol. (1166 p.) |
| Collection : | Pearson series in artificial intelligence |
| Sujets : |
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| 200 | 1 | |a Artificial intelligence |e a modern approach |f Stuart J. Russell and Peter Norvig | |
| 205 | |a Fourth edition, global edition | ||
| 214 | 0 | |a Harlow |c Pearson education limited | |
| 214 | 4 | |d C 2022 | |
| 215 | |a 1 vol. (1166 p.) |c ill., fig., couv ill. en coul. |d 25 cm | ||
| 225 | 2 | |a Pearson series in artificial intelligence | |
| 330 | |a Adapation autorisée de la 4e édition du même titre parue aux États-unis, ISBN 978-0-13-461099-3, Pearson education (C 2021)The long-anticipated revision of Artificial Intelligence: A Modern Approach explores the full breadth and depth of the field of artificial intelligence (AI). The 4th Edition brings readers up to date on the latest technologies, present concepts in a more unified manner, and offers new or expanded coverage of machine learning, deep learning, transfer learning, multi agent systems, robotics, natural language processing, causality, probabilistic programming, privacy, fairness, and safe AI. |2 Site web de l'éditeur | ||
| 359 | 2 | |b Part I: Artificial Intelligence |c 1. Introduction |c 2. Intelligent Agents |b Part II: Problem Solving |c 3. Solving Problems by Searching |c 4. Search in Complex Environments |c 5. Constraint Satisfaction Problems |c 6. Adversarial Search and Games |b Part III: Knowledge, Reasoning and Planning |c 7. Logical Agents |c 8. First-Order Logic |c 9. Inference in First-Order Logic |c 10. Knowledge Representation |c 11. Automated Planning |b Part IV: Uncertain Knowledge and Reasoning |c 12. Quantifying Uncertainty |c 13. Probabilistic Reasoning |c 14. Probabilistic Reasoning over Time |c 15. Making Simple Decisions |c 16. Making Complex Decisions |c 17. Multiagent Decision Making |c 18. Probabilistic Programming |b Part V: Machine Learning |c 19. Learning from Examples |c 20. Knowledge in learning |c 21. Learning probabilistic models |c 22. Deep learning |c 23. Reinforcement learning |b Part VI: Communicating, perceiving, and acting |c 24: Natural Language Processing |c 25: Deep Learning for Natural Language Processing |c 26: Robotics |c 27: Computer vision |b VII Conclusions |c 28: Philosophy, ethics, and safety of AI |c 29The future of AI | |
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