Showing papers in "Artificial Intelligence in 1978"

TL;DR: A general method of computer-assisted medical decision-making based on causal-associational network (CASNET) models of disease based on observations of a patient, pathophysiological states, and disease classifications for diagnosis and treatment of the glaucomas has been developed.

TL;DR: In this article, the authors describe the design of each program in the context of the chemical inference problems the program solves, and some chemical results produced by the programs are mentioned, as well as some results obtained by the program.

TL;DR: The BELIEVER system is presented by specifying a plan recognition process and its knowledge sources and can account for goal-directed actions that may succeed or fail in accomplishing the goal, as well as actions governed by norms.

TL;DR: The authors discuss the incorporation of richer semantic structures into the Preference Semantics system: they are called pseudo-texts and capture some of the information expressed in one type of frame proposed by Minsky (q.v.).

TL;DR: The case study illustrates why an exhaustive model-driven approach, which operates primarily by ruling out all the wrong answers, is a good approach for this domain.

TL;DR: A program which understands simple stories about painting and makes heavy use of real world knowledge is described, and there is an extensive discussion of various issues in knowledge representation and how they affect frame representations: modularity, the need for problem solving, worldly vs control knowledge, and cleanliness.

TL;DR: A body of program synthesis knowledge dealing with array operations, space reutilization, the divide-and-conquer paradigm, conversion from recursive paradigms to iterative paradigsms, and ordered set enumerations is presented.

TL;DR: In this paper, a transfer frame stands between the source and the destination and determines what information is allowed to pass from one to the other, and the transfer frame requires two steps: hypothesis and filtering.

TL;DR: The problems discussed and solutions presented are closely related to the more general problem of how to respond to a natural language input that surpasses the computer's model of language or of context.

TL;DR: SECS is an interactive program to assist a chemist in heuristically searching and evaluating the space of good synthetic pathways and develops synthetic plans using a logic-centered backward analysis from the target structure.

TL;DR: The branching factor of the alpha-beta pruning algorithm is shown to grow with n as @Q(n/lnn), therefore confirming a claim by Knuth and Moore that deep cut-offs only have a second order effect on the behavior of the algorithm.

TL;DR: It can be seen that a great deal of worthwhile material has now been generated about computer chess, but there is also quite a bit of nonsense by persons who have never built a program.

TL;DR: A program which proves theorems in set theory by the use of heuristics, which has been used to prove about 150 theorem in more and axiomatic set theory, sampling with functions, orderings, congruence relations and ordinal numbers.

TL;DR: A prototype extensible deductive system for elementary set theory which is based on truth-value preserving transformations is described and an experimental application of it to the first few chapters of W. V. O. Quine's book: Set Theory and its Logic.

TL;DR: This paper describes a system for automatically answering questions about a collection of natural language medical records that involves manual determination of a suitable tabular structure for representing the information contained in the medical records.

TL;DR: An extension of a mechanics problem solving program to the set of ''roller coaster'' problems, i.e. problems about the motion of a particle on a complex path, is described and compared to earlier work in this domain.