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Challenge to Artificial Intelligence: Programming Problems to be Solved

Classics

This paper is in the nature of a challenge to artificial intelligence experts. It suggests that the techniques of artificial intelligence should be applied to some realistic problems which exist in the programming and data processing fields. After a brief review of the little related existing work which has been done, the characteristics of programming problems which make them suitable for the application of artificial intelligence techniques are given. Specific illustrations of problems are provided under the broadcategories of data structure and organization, program structure and organization, improvements and corrections of programs, and language.In IJCAI-71: INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE. British Computer Society, London.


Analysis of curved line drawings using context and global information

Classics

We describe the analysis of visual scenes consisting of black on white drawings formed with curved lines, depicting familiar objects and forms: houses, trees, persons, and so on; for instance, drawings found in coloring books. The goal of such analysis is to recognize (by computer) such forms and shapes when present in the input scene; that is, to name (correctly) as many parts of the scene as possible: finger, hand, girl, dance, and so on. Complications occur because each input scene contains several such objects, partially occluding each other and in varying degrees of orientation, size, and so on. The analysis of these line drawings is an instance of'the context problem', which can be stated as'given that a set (a scene) is formed by components that locally (by their shape) are ambiguous, because each shape allows a component to have one of several possible values (a circle can be sun, ball, eye, hole) or meanings, can we make use of context information stated in the form of models, in order to single out for each component a value in such manner that the whole set (scene) is consistent or makes global sense?' Thus, shape drastically limits the values that a component could have, and further disambiguation is possible only by using global information (derived from several components and their interrelations or interconnections) under the assumption that the scene as a whole is meaningful. This paper proposes a way to solve'the context problem' in the paradigm of coloring book drawings. We have not implemented this approach; indeed, a purpose of this paper is to collect criticisms and suggestions.


A General Game-Playing Program

Classics

A general game-playing program must know the rules of the particular playing game. These rules are:(1) an algorithm indicating the winning state;(2) an algorithm enumerating legal moves. A move gives a set of changes from the present situation.There are two means of giving these rules:(1) We can write a subroutine which recognizes if we have won and another which enumerates legal moves. Such a subroutine is a black box giving to the calling program the answer: 'you win' or 'you do not win', or the list of legal moves. But it cannot know what is in that subroutine.(2) We can also define a language in which we describe the rules of a game. The program investigates the rules written with this language and finds some indications to improve its play. Artificial Intelligence and Heuristic Programming Edinburgh University Press



A computer-assisted study of Go on m X n boards

Classics

The game of Go invites analysis. The rules seem few and simple, suggesting that the game may have helpful theorems. Tens of millions of people play and skill has developed over centuries to extraordinary levels. Thus, computer analysis can be tested against analysis by highly skilled human players. We study M × N boards, rather than the usual 19 × 19.




Some Speculation about Artificial Intelligence and Legal Reasoning

Classics

Arguably the first article discussing the uses of AI in the law beyond straightforward information retrieval.Although the computer has worked its way out of the laboratory and into common experience, lawyers have made slim progress towards finding useful computer applications. Research in artificial intelligence, a branch of computer science, has illuminated our capacity to use computers to model human thought processes. This research suggests that computer science may assist lawyers in both the study and performance of their reasoning processes. In this Article we will argue that the time has come for serious interdisciplinary work between lawyers and computer scientists to explore the computer's potential in law.Stanford Law Review vol.23, no.1, November, 1970


AI: Will artificial intelligence ever rival human thinking? - MarketExpress

#artificialintelligence

Some of the world's most advanced artificial intelligence (AI) systems, at least the ones the public hear about, are famous for beating human players at chess or poker. Other algorithms are known for their ability to learn how to recognize cats or their inability to recognize people with darker skin. But are current AI systems anything more than toys? Sure, their ability to play games or identify animals is impressive, but does this help toward creating useful AI systems? To answer this, we need to take a step back and question what the goals of AI are.