K.A.PATON 411 24 Centromere finding: some shape descriptors for small chromosome outlines.

Networks as models of word storage: G. R. Kiss

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.

It has been argued by Hartley and Sleeman.

This paper reports the results obtained with a group of 24 14-year-old pupils when presented with sets of algebra tasks by the Leeds Modelling System.

This manual describes a domain-independent system, called EMYCIN, for constructing one class of expert computer programs: rule-based consultants. The resulting programs use knowledge specific to a problem domain to provide consultative advice to a client. The system-building tool, EMYCIN, is based on the domain-independent core of the MYCIN program. Domain kno,./ledge is represented in EMYCIN systems primarily as production rules, which are applied by a goal-directed backwardchaining control structure. Rules and consultation data may have associated measures of certainty, and incomplete data entry is allowed. The system includes an explanation facility that can display the line of reasoning followed by the consultation program, and answer questions from the client about the contents of its knowledge base. To aid the system designer in producing a knowledge base for a domain quickly and accurately, EMYCIN provides the following features: (1) a terse.

The Imitation Game I propose to consider the question, "Can machines think?" This should begin with definitions of the meaning of the terms "machine" and "think." The definitions might be framed so as to reflect so far as possible the normal use of the words, but this attitude is dangerous. If the meaning of the words "machine" and "think" are to be found by examining how they are commonly used it is difficult to escape the conclusion that the meaning and the answer to the question, "Can machines think?" is to be sought in a statistical survey such as a Gallup poll. Instead of attempting such a definition I shall replace the question by another, which is closely related to it and is expressed in relatively unambiguous words. The new form of the problem can be described in terms of a game which we call the "imitation game." It is played with three people, a man (A), a woman (B), and an interrogator (C) who may be of either sex. The interrogator stays in a room apart' from the other ...

How could one represent with a single prototype the class of figures which have an even number of disconnected parts?

This is an attempt to analyze attitudes and arguments brought forth by questions like "Can machines think?" and "Can machines exhibit intelligence?" Its purpose is to improve the climate which surrounds research in the field of machine or artificial intelligence. Its goal is not to convince those who answer the above questions negatively that they are ative wrong (although an attempt will be made to refute some of the neg arguments) but that they should be tolerant of research investigating these questions. Samuel Butler (1835-1902), in Erewhon and Erewhon Revisited (1933), concocted a civil war between the "machinists" and the "antimachinists." Butler stated "there is no security against the ultimate development of mechanical consciousness in the fact of machines possessing little consciousness now" and specylated that the time might come when "man shall become to the The topic came into prominence in the late 1940's when Babbage's dreams became a reality with the completion of the first large digital computers. When the popular press applied the term "giant brains" to these machines, computer builders and users, myself included, immediately arose to the defense of the human intellect. We hastened metic to proclaim that computers did not "think"; they only did arith A. M. Turing, who earlier had written one of the most important papers In it he circumvented the problem of properly defining the words "machine" and "thinking" and examined instead the question of a game This is now known throughout the computer field as "Turing's Test." Discussion of machine intelligence died down (but not out) in the early and mid-1950s but has come back in the last several years stronger than ever before. In fact, it has recently invaded the pages of Science (Mac-Gowan, 1960; Wiener, 1960; Taube, 1960; Samuel, 1960b). Like Turing, I avoid defining "to think." This notion is certainly not new, for it has existed since plicit man first compared his mental abilities with another man's, and it is im in all of the positive arguments on machine intelligence. Psychologists long ago developed "intelligence quotient" tinuum, as a yardstick in this con Existing commercial jet transports cannot transport people from one lake to another. But men cannot carry the load that a jeep can nor can men move with the speed of the jeep. Similarly, comparisons can be made between men and machines in the continuum of thinking. If there is objection to the use of the word "thinking," then "ability But it must be admitted that there exists some con of behavior in which men and machines coexist and in which they can be compared.

How could one represent with a single prototype the class of figures which have an even number of disconnected parts?