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.

This paper describes some work on automatically generating finite counterexamples in topology, and the use of counterexamples to speed up proof discovery in intermediate analysis, and gives some examples theorems where human provers are aided in proof discovery by the use of examples.

A programming language based on sets; motivation and examples.

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

The equivalence problem for program schemes, or for programs, is reduced to the proving of a theorem in second-order logic. This work extends Manna's first-order logic reductions. Some examples of the technique are given together with a suggested method for obtaining proofs in special cases by firstorder methods. INTRODUCTION Several workers in recent years have considered using techniques and ideas of various mathematical theories of computation for proving interesting results about computer programs. This paper is concerned with two of these approaches.

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

Psychological theory attempts to explain how thinking--the subject matter of psychology--is possible by a brain composed of single mechanistic elements--the basic assumption of psychology. The problem of programming digital computers to behave in complex fashions is equivalent to this aspect of the psychological problem. Today automata theorists agree that no fundamental barrier blocks the development of machines which can think, by any reasonable definition of the term. However, the precise techniques for implementing general thinking proceGseE-J have been only partially developed. An example of a high-level, general thinking process is comprehension: the understanding of passages of a natural language.

Current subprojects include applications of the program Gerring.

Although computer-based instruction has become widely available as a learning aid in medical education, few physicians interact with educational programs after they have left medical school. Some notable exceptions occur when specially prepared computer programs are made available by vendors or program committees at annual clinical meetings. Yet this kind of learning tool is seldom used by practicing physicians at other times during the year. In this paper, I would like to consider ways in which computer-based education might be more effectively integrated into the clinical activities of the practicing physician, and to outline some of the technological and psychological barriers to their successful implementation.

The duraticn of the neuro'ogical signs is 7.2 hours.