Government
11 An Experiment in Automatic Induction R. J. Popplestone
INTRODUCTION The problem discussed in this paper, namely that of finding a function to satisfy a given argument-value table, is by no means new to computing science, or to mathematics. Thus, for example, the problem of fitting a curve to a set of points is a part of numerical analysis. However, I am concerned with finding a function over a non-metric space, and so my work is closer to that of Feldman et al. (1969) in what they call, 'grammatical inference' or to the automaton-synthesizing programs described by Fogel, Owens and Walsh (1966). There have been some applications of learning devices. Perhaps the best known is Samuel's checkers program (Samuel 1967), but Murray and Elcock (1968) have a system for describing generalized board states in Go-Moku that employs a much richer language to describe the concepts learnt.
MECHANIZED REASONING
We will define the notions of abstract theorem-proving graph, abstract theorem-proving problem g and search strategy E for g. These concepts generalize the usual tree (or graph) searching problem and admit Hart, Nilsson and Raphael (1968) and Pohl (1969) theories of heuristic search. In particular the admissibility and optimality theorems of Hart, Nilsson and Raphael generalize for the classes 0 and 0" of diagonal search strategies for abstract theorem-proving problems. In addition the subclass au of 0 is shown to be optimal for 2. Implementation of diagonal search is treated in some detail for theorem-proving by resolution rules (Robinson 1965). SEARCH STRATEGIES, COMPLETENESS AND EFFICIENCY Completeness and efficiency of proof procedures can be studied only in the context of search strategies. A system T of inference rules and axioms can be complete or incomplete for a given class of intended interpretations. Similarly a search strategy E for T may or may not be complete for ...
Machine Intelligence 4
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.
10 On Representations of Problems of Reasoning about Actions Saul Amarel
The general problem of re-Presentation is concerned with the relationship between different ways of formulating a problem to a problem solving system and the efficiency with which the system can be expected to find a solution to the problem. An understanding of the relationship between problem formulation and problem solving efficiency is a prerequisite for the design of procedures that can automatically choose the most appropriate' representation of a problem (they can find a point of view' of the problem that maximally simplifies the process of finding a solution). Many problems of practical importance are problems of reasoning about actions. In these problems, a course of action has to be found that satisfies a number of specified conditions. A formal definition of this class of problems is given in the next section, in the context of a general conceptual framework for formulating these problems for computers. Everyday examples of reasoning about actions include planning an airplane trip, organizing a dinner party, etc. There are many examples of industrial and military problems in this category, such as scheduling assembly and transportation processes, designing a program for a computer, planning a military operation, etc. The research presented in this paper was sponsored in part by the Air Force Office of Scientific Research, under Contract Number A F49(638)-1184. Part of this work was done while the author was on a visiting appointment at the Computer Science Department of the Carnegie Institute of Technology, Pittsburgh, Pa.
Stanford Heuristic Programming Project December 1984 Report No. HPP-84-44
Thi3 framework generalizes previous work on cooperation without communication, and shows the ability of communication to resolve conflicts among agents having disparate goals. Using a deal-making mechanism, agents are able to coordinate and cooperate more easily than in the communication-free model. In addition, there are certain types of interactions where communication makes possible mutually beneficial activity that is otherwise impossible to:oordinate.