Exploring Artificial Intelligence: Survey Talks from the National Conferences on Artificial IntelligenceHoward E. Shrobe "Exploring Artificial Intelligence" is a unique presentation of the spectrum of research in Artificial Intelligence. Each self-contained chapter is based on a survey talk given at the National Conferences on Artificial Intelligence (AAAI 1986 & 1987). The original speakers, all leading researchers in their fields, have updated and revised their talks especially for this publication. Selected and edited to be accessible to students and nonspecialists, "Exploring Artificial Intelligence" preserves the informal character of the talks while presenting authoritative overviews of current research in critical subareas of AI. Individually, each lecture provides a penetrating exploration of a key area. Taken together, they offer a panorama of the field as a whole: its core issues, progress, and future directions. An ideal collection for personal reference or for use in introductory courses in AI and its subfields, "Exploring Artificial Intelligence" is essential reading for anyone interested in the intellectual and technological challenges of Artificial Intelligence. |
Contents
An Introduction to Explanationbased Learning | 45 |
INTERACTING THROUGH LANGUAGE | 81 |
NaturalLanguage Interfaces | 133 |
Copyright | |
13 other sections not shown
Other editions - View all
Common terms and phrases
abstraction action algorithm alpha-beta pruning analysis approach Artificial Intel Artificial Intelligence Automated axioms behavior branching factor breadth-first search brute-force search cache causal clause CLOS Cognitive complete component Computer Science concept Conference on Artificial constraints data type database deduction default defined depth-first search developed device diagnosis disease domain theory example Figure Forbus formal formulas frame problem function goal grammar graph heuristic hypotheses implementation inference input intelligent tutoring systems interaction International Joint Conference interpretation Kleer knowledge learning LISP logic machine Machine Learning memory metaclass method model-based Morgan Kaufmann Publishers natural language nodes object operator performance pointer predictions problem Proceedings processor PROLOG proof qualitative physics query represent representation requires result rules San Mateo semantic sentence simulation situation calculus solution solving specific structure symbolic computing syntactic task techniques temporal temporal logic tion tree Tutor variables