Showing papers in "Artificial Intelligence in 1980"

TL;DR: The authors formalizes such conjectural reasoning and shows that the objects they can determine to have certain properties or relations are the only objects that do, which is a common assumption in human and intelligent computer programs.

TL;DR: In this article, the authors explore the number of tree search operations required to solve binary constraint satisfaction problems and show that the two principles of first trying the places most likely to fail and remembering what has been done to avoid repeating the same mistake twice improve the standard backtracking search.

TL;DR: It is argued that DCGs can be at least as efficient as ATNs, whilst the DCG formalism is clearer, more concise and in practice more powerful.

TL;DR: This paper presents an approach to hierarchical planning, termed constraint posting, that uses constraints to represent the interactions between subproblems and is illustrated with a computer program that plans gene-cloning experiments in molecular genetics.

TL;DR: An interactive system organized around networks of constraints rather than the programs which manipulate them is presented, and a language of hierarchical constraint networks is described, one method of deriving useful consequences of a set of constraints which is called propagation.

TL;DR: This is an informal description of my ideas about using formal logic as a tool for reasoning systems using computers, illustrated by the features of FOL.

TL;DR: In this paper, the authors propose a framework for viewing issues of knowledge indexing and retrieval, a framework that includes what appears to be a useful perspective on the concept of a strategy.

TL;DR: Builders of expert rule-based systems attribute the impressive performance of their programs to the corpus of knowledge they embody: a large network of facts to provide breadth of scope, and a large array of informal judgmental rules which guide the system toward plausible paths to follow and towards implausible ones.

TL;DR: In this article, a labeling procedure for the Origami world is proposed, which can find the 3D meaning of a given line drawing by assigning one of the labels, + (convex edge), − (concave edge), ←, and → (occluding boundary) to each line.

TL;DR: Cooperating local parallel processes can be used as aids in assigning numerical or symbolic labels to image or scene parts in low-level vision.

TL;DR: It is shown that a game with WIN-LOSS terminals can be solved by examining, on the average, O [(d) h 2 ] terminal positions if positions if P 0 ≠ P∗ and O [(P∗ (1 − P ∗) ) h ] positionsif P 0 = P∷, the former performance being optimal for all search algorithms.

TL;DR: An effort to automate the debugging of real programs is presented and the main characteristics of LAURA are the representation of programs by graphs, which gets rid of many syntactical variations, the use of program transformations, realized on the graphs, and its heuristic strategy to identify step by step the elements of the graphs.

TL;DR: The design of BLAH, ta system which combines a reasoning capability with an explanation capability is described, which is designed to take account of certain features needed in generating an acceptable explanation, such as the user's expectations.

TL;DR: The first steps in the development of a computer model of the process of changing representations in problem solving are presented, and a language for expressing representations and an interpreter for applying the transformations to representations have been developed.

TL;DR: A program, PARADISE (PAttern Recognition Applied to DIrecting SEarch), which finds the best move in tactically sharp middle game positions from the games of chess masters, encodes a large body of knowledge in the form of production rules.

TL;DR: An algorithm is presented, with correctness proof, which computes multilevelcounterfactuals by recursively reducing the original induction problem to a smaller ‘residual’ problem, whose generalization gives the desired counterfactual.

TL;DR: Part I of this memo discusses minimal entailment and minimal completion suggested by McCarthy (now included in his more general notion of circumscription) and Part II discusses the “non-monotonic logic” of McDermott and Doyle.

TL;DR: This paper examines the scientific issues involved in constructing the program, an analysis of its performance, and the scientific significance of the win and presents the SNAC method of constructing evaluation functions.

TL;DR: It is argued that the goal-expectation setting, created from an analysis of personality traits attributed to actors in a story, establishes a best-first evaluation criterion that makes more tractable the search problem inherent in story understanding.

TL;DR: A number of strategies for the synthesis of algorithms from a given input-output specification of a problem are presented which are centered around a few basic principles as discussed by the authors, which have been verified for more than ten different algorithms.

TL;DR: This paper analyzes the number of nodes expanded by A∗ as a function of the accuracy of its heuristic estimates by treating the errors h∗ - h as random variables whose distributions may vary over the nodes in the graph.

TL;DR: While there are many ways to implement refinement, it is suggested that one particular technique—which is called content reference—offers a number of advantages, including giving the system some ability to reason about the content of its knowledge.

TL;DR: An algorithm is presented which combines local sensory probing with knowledge of labeling constraints to proceed directly to a labeling analysis of a given scene and produces a measure for the complexity of line drawings.

TL;DR: It is argued that theorem provers based on domain dependent knowledge must be able to increase their domain dependent deductive knowledge if they are to serve as a component of a mathematical reasoning system.

TL;DR: This paper shows how the side effects of segments can be derived and constructively used in achieving the required goal, and in guaranteeing the correctness of the resulting program.