9780898381856 - An Artificial Intelligence Approach to Test Generation (The Springer International Series in Engineering and Computer Science, 19, Band 19) von Singh, Narinder (5 Ergebnisse)

Hardcover. Zustand: Bon. Ancien livre de bibliothèque. Traces d'usure sur la couverture. Couverture différente. Edition 1987. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Good. Former library book. Signs of wear on the cover. Different cover. Edition 1987. Ammareal gives back up to 15% of this item's net price to charity organizations.

Hardcover. Zustand: Très bon. Ancien livre de bibliothèque. Petite(s) trace(s) de pliure sur la couverture. Légères traces d'usure sur la couverture. Salissures sur la tranche. Couverture différente. Edition 1987. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisat ENGLISH DESCRIPTION Book Condition: Used, Very good. Former library book. Slightly creased cover. Slight signs of wear on the cover. Stains on the edge. Different cover. Edition 1987. Ammareal gives back up to 15% of this item's net price to charity organizations.

Zustand: New. In.

Zustand: New. Series: The Springer International Series in Engineering and Computer Science. Num Pages: 194 pages, biography. BIC Classification: UYQE. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly. Dimension: 235 x 155 x 12. Weight in Grams: 476. . 1987. Hardback. . . . . Books ship from the US and Ireland.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - I am indebted to my thesis advisor, Michael Genesereth, for his guidance, inspiration, and support which has made this research possible. As a teacher and a sounding board for new ideas, Mike was extremely helpful in pointing out Haws, and suggesting new directions to explore. I would also like to thank Harold Brown for introducing me to the application of artificial intelligence to reasoning about designs, and his many valuable comments as a reader of this thesis. Significant contribu tions by the other members of my reading committee, Mark Horowitz, and Allen Peterson have greatly improved the content and organization of this thesis by forcing me to communicate my ideas more clearly. I am extremely grateful to the other members of the Logic Group at the Heuristic Programming Project for being a sounding board for my ideas, and providing useful comments. In particular, I would like to thank Matt Ginsberg, Vineet Singh, Devika Subramanian, Richard Trietel, Dave Smith, Jock Mackinlay, and Glenn Kramer for their pointed criticisms. This research was supported by Schlumberger Palo Alto Research (previously Fairchild Laboratory for Artificial Intelligence). I am grateful to Peter Hart, the former head of the AI lab, and his successor Marty Tenenbaum for providing an excellent environment for performing this research.