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Artificial Intelligence: A General Survey (The Lighthill Report)
Selected quotes:"The Science Research Council has been receiving an increasing number of applications for research support in the rather broad field with mathematical engineering and biological aspects which often goes under the general description Articial Intelligence (Al). The research support applied for is sufficient in volume, and in variety of discipline involved, to demand that a general view of the field be taken by the Council itself.""To supplement the important mass of specialist and detailed information available to the Science Research Council its Chairman decided to commission an independent report by someone outside the Al field but with substantial general experience of research work in multidisciplinary fields including fields with mathematical, engineering and biological aspects."-----"Most workers in Al research and in related elds confess to a pro nounced feeling of disappointment in what has been achieved in the past twenty-five years. Workers entered the feld around 1950, and even around 1960, with high hopes that are very far from having been realised in 1972. In no part of the field have the discoveries made so far produced the major impact that was then promised.""In the meantime, claims and predictions regarding the potential results of Al research had been publicised which went even farther than the expectations of the majority of workers in the field whose embarrassments have been added to by the lamentable failure of such inflated predictions.""These general statements are expanded in a little more detail in the rest of section 3, which has been influenced by the views of large numbers of people listed in section 1 but which like the whole of this report represents in the last analysis only the personal view of the author. Before going into such detail he is inclined, as a mathematician, to single out one rather general cause for the disappointments that have been experienced: failure to recognise the implications of the 'combinatorial explosion'."See also: BBC TV - June 1973 - Lighthill Controversy Debate at the Royal Institution with Professor Sir James Lighthill, Professor Donald Michie, Professor Richard Gregory and Professor John McCarthy.Also in Lighthill, J., Sutherland, N. S., Needham, R. M., Longuet-Higgins, H. C., and Michie, D. (Eds.), Artificial Intelligence: A Paper Symposium. Science Research Council of Great Britain.
Learning and executing generalized robot plans
Fikes, R.E. | Hart, P.E. | Nilsson, N.J.
"In this paper we describe some major new additions to the STRIPS robot problem-solving system. The first addition is a process for generalizing a plan produced by STRIPS so that problem-specific constants appearing in the plan are replaced by problem-independent parameters.The generalized plan, stored in a convenient format called a triangle table, has two important functions. The more obvious function is as a single macro action that can be used by STRIPS—either in whole or in part—during the solution of a subsequent problem. Perhaps less obviously, the generalized plan also plays a central part in the process that monitors the real-world execution of a plan, and allows the robot to react "intelligently" to unexpected consequences of actions.We conclude with a discussion of experiments with the system on several example problems."Artificial Intelligence 3:251-288
A Paradigm for Reasoning by Analogy
A paradigm enabling heuristic problem solving programs to exploit an analogy between a current unsolved problem and a similar but previously solved problem to simplify it s search for a solution is outlined. It is developed in detail for a first-order resolution logic theorem prover. Descriptions of the paradigm, implemented LISP programs, and preliminary experimental results are presented. This is believed to be the firs t system that develops analogical information and exploits it so that a problem-solving program can speed its search.IJCAI-71, British Computer Society, London, 1971. Revised version in Artificial intelligence 2(2):147- 178, fall, 1971.
Challenge to Artificial Intelligence: Programming Problems to be Solved
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.
STRIPS: A New Approach to the Application of Theorem Proving to Problem Solving
Reprinted in Readings in Planning, edited by J. Allen, J. Hendler, and A. Tate, Morgan Kaufmann Publishers, San Mateo, California, 1990. Also Reprinted in Computation and Intelligence: Collected Readings, edited by George F. Luger, AAAI Press, 1995. See also: Artificial Intelligence, Volume 2, Issues 3–4, Winter 1971, Pages 189–208 In IJCAI-71: INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE. British Computer Society, London.. Revised version in Artificial Intelligence, 2(3), pp 189-208.
A net structure for semantic information storage, deduction and retrieval
This paper describes a data structure, MENS (MEmory Net Structure), that is useful for storing semantic information stemming from a natural language, and a system, MENTAL (MEmory Net That Answers and Learns) that interacts with a user (human or program), stores information into and retrieves information from MENS and interprets some information in MENS as rules telling it how to deduce new information from what is already stored. MENTAL can be used as a guestion-answering system with formatted input/output, as a vehicle for experimenting with various theories of semantic structures or as the memory management portion of a natural language question-answering system.See also:U. Wisconsin Technical Report 109 versionScanned, non-OCR, versionIn IJCAI-71: INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE. British Computer Society, London, pp. 512-523.