Plotting

 McCarthy, John



We Need Better Standards for Artificial Intelligence Research: President's Message

AI Magazine

The state of the art in any science includes the criteria for evaluating research. Like every other aspect of the science, it An example is the alpha-beta heuristic for game playing. The criteria for evaluating AI research Humans use it, but it wasn't identified by the writers of the are not in very good shape. I had intended to produce four first chess programs. It doesn't constitute a game playing presidential messages during my term but have managed only program, but it seems clearly necessary, because without two, because this one has proved so difficult to write.


Artificial Intelligence Needs More Emphasis on Basic Research: President's Quarterly Message

AI Magazine

Too few people are doing basic research in AI relative to the number working on applications. The ratio of basic/applied is less in AI than in the older sciences and than in computer science generally. This is unfortunate, because reaching human level artificial intelligence will require fundamental conceptual advances.


Artificial Intelligence Needs More Emphasis on Basic Research: President's Quarterly Message

AI Magazine

AI NEEDS MORE EMF'HASIS ON BASIC RESEARCH Too few people are doing basic research in AT rela-language processing seems misguided to me. There is too tive to the number working on applications The ratio of much emphasis on syntax and not enough on the semantics. This is unfortunate, between existing AI formalisms and English miss the point. Even the applied goals press in English what we already know how to express in proposed by various groups in the U.S., Europe and Japan computerese. Rather we must study those ideas expressible for the next ten years are not just engineering extrapolations in natural language that no-one knows how to represent at from the present state of science.


Research in Progress in Robotics at Stanford University

AI Magazine

The Robotics Project (the "Hand-Eye Project") evolved within the Stanford Artificial Intelligence Laboratory under the guidance of John McCarthy, Les Earnest, Jerry Feldman, and Tom Binford. Major efforts have been undertaken to isolate and solve fundamental problems in computer vision, manipulation, and autonomous vehicles. Stereo vision and texture have been examined. Several generations of robot programming languages have resulted in AL, an intermediate-level language for commanding manipulation.


Research in Progress in Robotics at Stanford University

AI Magazine

The Robotics Project (the "Hand-Eye Project") evolved within the Stanford Artificial Intelligence Laboratory under the guidance of John McCarthy, Les Earnest, Jerry Feldman, and Tom Binford. Major efforts have been undertaken to isolate and solve fundamental problems in computer vision, manipulation, and autonomous vehicles. Generalized cones were introduced for modeling the geometry of 3-dimensional objects, and programs were constructed which learned structural descriptions of objects from laser-ranging data ("structured light"). Stereo vision and texture have been examined. Several generations of robot programming languages have resulted in AL, an intermediate-level language for commanding manipulation. A computer-controlled roving vehicle ("the cart") detected obstacles (using 9-eyed stereo) and planned paths to avoid them.


Circumscription - A form of non-monotonic reasoning

Classics

"Circumscription is a rule of conjecture that can be used by a person or program for `jumping to certain conclusions'. Namely, the objects that can be shown to have a certain property P by reasoning from certain facts A are all the objects that satisfy P. More generally, circumscription can be used to conjecture that the tuples that can be shown to satisfy a relation P(x, y, z) are all the tuples satisfying this relation. Thus we circumscribe the set of relevant tuples."Artificial Intelligence 13:27-39. Also in Readings in Artificial Intelligence, B.L. Webber and N.J. Nilsson (eds.), Tioga Publishing, 1981.


Epistemological Problems of Artificial Intelligence

Classics

"The epistemological part of Al studies what kinds of facts about the world are available to an observer with given opportunities to observe, how these facts can be represented in the memory of a computer, and what rules permit legitimate conclusions to be drawn from these facts. It leaves aside the heuristic problems of how to search spaces of possibilities and how to match patterns."See also: IJCAI 5, 1038-1044In Readings in Artificial Intelligence, B.L. Webber and N.J. Nilsson (eds.), Tioga Publishing, 1981.


A Tough Nut for Theorem Provers

Classics

"It is well known to be impossible to tile with dominoes a checkerboard with two opposite corners deleted. This fact is readily stated in the first order predicate calculus, but the usual proof which involves a parity and counting argument does not readily translate into predicate calculus. We conjecture that this problem will be very difficult for programmed proof procedures."Stanford Artificial Intelligence Project Memo No. 16