An Algorithmic Perspective on Imitation Learning - Couverture souple

Osa, Takayuki; Pajarinen, Joni; Neumann, Gerhard; Bagnell, J. Andrew; Abbeel, Pieter

Couverture souple

ISBN 10 : 168083410X ISBN 13 : 9781680834109

Editeur : now publishers Inc, 2018

Synopsis

As robots and other intelligent agents move from simple environments and problems to more complex, unstructured settings, manually programming their behavior has become increasingly challenging and expensive. Often, it is easier for a teacher to demonstrate a desired behavior rather than attempt to manually engineer it. This process of learning from demonstrations, and the study of algorithms to do so, is called imitation learning. An Algorithmic Perspective on Imitation Learning provides the reader with an introduction to imitation learning. It covers the underlying assumptions, approaches, and how they relate; the rich set of algorithms developed to tackle the problem; and advice on effective tools and implementation. An Algorithmic Perspective on Imitation Learning serves two audiences. First, it familiarizes machine learning experts with the challenges of imitation learning, particularly those arising in robotics, and the interesting theoretical and practical distinctions between it and more familiar frameworks like statistical supervised learning theory and reinforcement learning. Second, it provides roboticists and experts in applied artificial intelligence with a broader appreciation for the frameworks and tools available for imitation learning. It pays particular attention to the intimate connection between imitation learning approaches and those of structured prediction.

Détails de l'édition

• Éditeur: now publishers Inc
• Date d'édition: 2018
• Langue: anglais
• ISBN 10: 168083410X
• ISBN 13: 9781680834109
• Reliure: Broché
• Nombre de pages: 194
• Coordonnées du fabricant: non disponible
• Personne responsable: non disponible