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PEARSON EDUCATION Intelligence artificielle - 4e édition: Une approche moderne

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Description

Ecrit par des experts de renommée mondiale, ce livre est la référence incontournable en matière d'intelligence artificielle (IA) dont il présente et analyse tous les concepts : logique, probabilités, mathématiques discrètes et du continu, perception, raisonnement, apprentissage, prise de décision et action. Un traitement approfondi des sujets simples comme des sujets avancés permet aux étudiants d'acquérir une compréhension générale des frontières de l'IA sans compromettre ni la complexité et ni la rigueur. Sa spécificité est de présenter l'IA à travers le concept d'agent intelligent. Les auteurs exposent comment un système réussit à percevoir son environnement de manière à analyser ce qui s'y passe, et comment il transforme la perception qu'il a de son environnement en actions concrètes. Cette approche intégratrice montre comment les différents sous-domaines de l'IA se combinent pour construire des applications capables de répondre à la complexité du monde réel. De plus, un très grand nombre de renvois entre les sections expose les connexions entre des domaines qui sont le plus souvent présentés comme indépendants. Parmi les sujets couverts : - les contributions des mathématiques, de la théorie des jeux, de l'économie, de la théorie des probabilités, de la psychologie, de la linguistique et des neurosciences - les différentes manières de représenter formellement les connaissances relatives au monde qui nous entoure ainsi que le raisonnement logique fondé sur ces connaissances - les méthodes de raisonnement qui permettent d'établir des plans et donc de proposer des actions à entreprendre - la prise de décisions en environnement incertain : réseaux bayésiens et algorithmes tels que l'élimination de variables et MCMC (Markov Chain Monte-Carlo) - les méthodes d'apprentissage automatique (machine learning) employées pour générer les connaissances nécessaires aux composants de prise de décision : boosting, EM (expectation-minimization), machines à vecteurs support, réseaux de neurones, apprentissage profond (deep learning) - la perception avec le traitement du langage naturel et la vision par ordinateur ainsi que l'action avec la robotique - l'avenir de l'IA et ses implications philosophiques et éthiques. Chaque chapitre est illustré par de nombreux exemples et schémas, puis se termine par un résumé. Les exercices se trouvent en anglais sur la plateforme dédiée à l'ouvrage. Cette 4e édition tient compte des derniers développements de la matière et présente les concepts de manière plus unifiée. Elle apporte un éclairage nouveau et couvre de manière élargie l'apprentissage automatique, l'apprentissage profond, l'apprentissage par transfert, les systèmes multi-agents, la robotique, le traitement du langage naturel, la causalité, la programmation probabiliste, le respect de la vie privée, l'équité et la sécurité.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
26 November 2021
Listed Since
13 April 2021

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