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Showing papers by "Nils J. Nilsson published in 1995"


Book
31 Oct 1995
TL;DR: In this article, the authors describe a problem solver called STRIPS that attempts to find a sequence of operators in a spcce of world models to transform a given initial world model into a model in which a given goal formula can be proven to be true.
Abstract: We describe a new problem solver called STRIPS that attempts to find a sequence of operators in a spcce of world models to transform a given initial world model into a model in which a given goal formula can be proven to be true. STRIPS represents a world n,~del as an arbitrary collection of first-order predicate calculus formulas and is designed to work with .models consisting of large numbers of formulas. It employs a resolution theorem prover to answer questions of particular models and uses means-ends analysis to guide it to the desired goal-satisfying model.

1,793 citations


Journal ArticleDOI
TL;DR: It is claimed that AI is now at the beginning of another transition, one that will reinvigorate efforts to build programs of general, humanlike competence, and these programs will use specialized performance programs as tools, much like humans do.
Abstract: In its early stages, the field of AI had as its main goal the invention of computer programs having the general problem-solving abilities of humans. Along the way, a major shift of emphasis developed from general-purpose programs toward performance programs, ones whose competence was highly specialized and limited to particular areas of expertise. In this article, I claim that AI is now at the beginning of another transition, one that will reinvigorate efforts to build programs of general, humanlike competence. These programs will use specialized performance programs as tools, much like humans do.

58 citations


Journal ArticleDOI
TL;DR: This note focuses on how to present a coherent view of the core subject matter of AI, which is to study AI's intellectual content, perhaps presenting related topics in psychology and philosophy.
Abstract: Several challenges confront the organizer of an introductory course in artificial intelligence (AI). First, one has to decide what subject matter to include. The union of everything in all of the popular AI textbooks is much too large, and the intersection undoubtedly won't include enough of what the organizer thinks important. The second challenge is how to blend the selected topics into a coherent whole. The third involves matters such as problem sets, programming exercises, laboratory work, case studies, and collateral readings. Finally, one must decide on the main purpose of the course: is it to teach AI techniques and skills, or is it to study AI's intellectual content, perhaps presenting related topics in psychology and philosophy? In this note we concentrate on the first and second of these topics---how to present a coherent view of the core subject matter of AI.

4 citations