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1 On Alan Turing and the Origins of Digital Computers B. Randell

AI Classics

This paper documents an investigation into the role that the late Alan Turing played in the development of electronic computers. Evidence is presented that during the war he was associated with a group that designed and built a series of special purpose electronic computers, which were in at least a limited sense'program controlled', and that the origins of several post-war general purpose computer projects in Britain can be traced back to these wartime computers. INTRODUCTION During my amateur investigations into computer history, I grew intrigued by the lack of information concerning the role played by the late Alan Turing.


MACHINE INTELLIGENCE 2

AI Classics

C. COOPER 21 3 Data representation--the key to conceptualisation: D. B. VIGOR 33 MECHANISED MATHEMATICS 45 4 An approach to analytic integration using ordered algebraic expressions: L. I. HODGSON 47 5 Some theorem-proving strategies based on the resolution principle: J. L DARLINGTON 57 MACHINE LEARNING AND HEURISTIC PROGRAMMING 73 6 Automatic description and recognition of board patterns in Go-Moku: A. M. MURRAY and E. W. Etcomc


MACHINE INTELLIGENCE 13

AI Classics

The two outstanding figures in the history of computer science are Alan Turing and John von Neumann, and they shared the view that logic was the key to understanding and automating computation. In particular, it was Turing who gave us in the mid-1930s the fundamental analysis, and the logical definition, of the concept of'computability by machine' and who discovered the surprising and beautiful basic fact that there exist universal machines which by suitable programming can be made to t This essay is an expanded and revised version of one entitled The Role of Logic in Computer Science and Artificial Intelligence, which was completed in January 1992 (and was later published in the Proceedings of the Fifth Generation computer Systems 1992 Conference). Since completing that essay I have had the benefit of extremely helpful discussions on many of the details with Professor Donald Michie and Professor I. J. Good, both of whom knew Turing well during the war years at Bletchley Park. Professor J. A. N. Lee, whose knowledge of the literature and archives of the history of computing is encyclopedic, also provided additional information, some of which is still unpublished. Further light has very recently been shed on the von Neumann side of the story by Norman Macrae's excellent biography John von Neumann (Macrae 1992). Accordingly, it seemed appropriate to undertake a more complete and thorough version of the FGCS'92 essay, focussing somewhat more on the interesting historical and biographical issues. I am grateful to Donald Michie and Stephen Muggleton for inviting me to contribute such a'second edition' to the present volume, and I would also like to thank the Institute for New Computer Technology (ICOT) for kind permission to make use of the FGCS'92 essay in this way. 1 LOGIC, COMPUTERS, TURING, AND VON NEUMANN


Logic, Computers, Turing, and von Neumannt J. A. Robinson

AI Classics

The two outstanding figures in the history of computer science are Alan Turing and John von Neumann, and they shared the view that logic was the key to understanding and automating computation. In particular, it was Turing who gave us in the mid-1930s the fundamental analysis, and the logical definition, of the concept of'computability by machine' and who discovered the surprising and beautiful basic fact that there exist universal machines which by suitable programming can be made to t This essay is an expanded and revised version of one entitled The Role of Logic in Computer Science and Artificial Intelligence, which was completed in January 1992 (and was later published in the Proceedings of the Fifth Generation computer Systems 1992 Conference). Since completing that essay I have had the benefit of extremely helpful discussions on many of the details with Professor Donald Michie and Professor I. J. Good, both of whom knew Turing well during the war years at Bletchley Park. Professor J. A. N. Lee, whose knowledge of the literature and archives of the history of computing is encyclopedic, also provided additional information, some of which is still unpublished. Further light has very recently been shed on the von Neumann side of the story by Norman Macrae's excellent biography John von Neumann (Macrae 1992). Accordingly, it seemed appropriate to undertake a more complete and thorough version of the FGCS'92 essay, focussing somewhat more on the interesting historical and biographical issues. I am grateful to Donald Michie and Stephen Muggleton for inviting me to contribute such a'second edition' to the present volume, and I would also like to thank the Institute for New Computer Technology (ICOT) for kind permission to make use of the FGCS'92 essay in this way. 1 LOGIC, COMPUTERS, TURING, AND VON NEUMANN


MACHINE INTELLIGENCE 11

AI Classics

In this paper we will be concerned with such reasoning in its most general form, that is, in inferences that are defeasible: given more information, we may retract them. The purpose of this paper is to introduce a form of non-monotonic inference based on the notion of a partial model of the world. We take partial models to reflect our partial knowledge of the true state of affairs. We then define non-monotonic inference as the process of filling in unknown parts of the model with conjectures: statements that could turn out to be false, given more complete knowledge. To take a standard example from default reasoning: since most birds can fly, if Tweety is a bird it is reasonable to assume that she can fly, at least in the absence of any information to the contrary. We thus have some justification for filling in our partial picture of the world with this conjecture. If our knowledge includes the fact that Tweety is an ostrich, then no such justification exists, and the conjecture must be retracted.




Communication and Cooperation Jeffrey S. Rosenschein Michael R. Genesereth *** REVISED DRAFT **

AI Classics

COMPUTER SCIENCE DEPARTMENT Stanford University Stanford, California 94305 Commu licaticn and Cooperation Abstract Intelligent agents need to coordinate their actions in pursuit of common goals. When communication is possible, cooperating agents must decide what information to pass in order to agree on a single course of action. This paper outlines several communication strategies (under monotonic and nonmonotonic planning assumptions), proving that some are convergent while others are not. An analysis is also made of the advantages of passing false information. Introduction Recent years have seen increasing interest in Distributed Artificial Intelligence (DAI) systems, that is, in groups of intelligent agents whose members cooperate in carrying out tasks. Considerable work has gone on in this area, producing a number of tentative approaches to cooperation; notable among these research efforts are Smith and Davis' work on the Contract Net [1], Davis' investigations of Cooperative Problem Solving strategies [2], Georgeff's approach to assuring non-interference among distinct agents' plans [3, 41, and Lesser and Corkill's empirical analyses of distributed computation 151. Despite some genuine insights that these researchers have gained, however, DAI has lacked much of the formal foundation needed for progress. Recent work by Appelt 161, Moore [7, 8] and Icon lige 19, 10, 11, 121 has begun to develop the formal descriptions necessary for one agent to reason about another agent's knowledge and beliefs; this is a key step in the development of successful DAI systems. This paper begins to lay the groundwork for another aspect of Distributed Artificial Intelligence's foundation; it presents a description and analysis of information pass:ng strategies between intelligent agents. Through use of a formal descriptive language, certain information passing behavior is proven to be convergent. In addition, an analysis is made of the role that can be played by the passing of false information, i.e., information that is logically inconsistent with the beliefs of the sender. Consider, for example, two individuals who have lost contact with each other in a department store [131.