Programming a model of human concept formulation (1995)

A model of human information processing during formation has been constructed, using a list processing, digital computer program. The program's input consists of descriptions of objects in terms of dimensions and values. The universe of objects is divided into two or more sets. The program attempts to form a decision rule, based upon descriptions of objects, which can be used to assign any previously presented or new object to its correct set.The program is a model for human information processing, rather than an artificial intelligence system. It contains features which limit number of objects in internal memory and number of dimensions which may be involved in an answer. Using this program, simulations have been performed of a number of psychological experiments in learning. Comparison of these simulations with data obtained from human subjects will be discussed.What is a concept? Ordinary usage is not precise. The English the of force, the of massive retaliation, and concept of are all permissible. Church has offered a definition which has been accepted, implicitly, by psychologists who perform concept experiments. Church's argument is that any given symbol (or name) can be attached to members of a set of objects. For any arbitrary object there exists a rule concerning description of object, a rule which can be used to decide whether or not object is a member of set of objects to which name applies. The decision rule is of name, set of objects is denotation of name.In a typical learning experiment subject is confronted with a series of stimuli which are given a particular name and another series of stimuli which are either given another particular name, or a series of different names. Thus first set might be called dogs and second either not-dogs or cats, wolves, sheep, etc. Thus some routines are necessary to classify instances to correspond to names assigned by experimenter. These are our ordering routines. Sometimes various stimuli given one name have certain common characteristics, e.g. all positive instances may have three triangles. At other times there are no common stimulus elements, but there are common relationships, e.g. all positive instances may have same size of upper figure as lower figure, although figures may be large, medium or small sized in each row. A machine routine may be required to describe relations between basic stimulus elements. So we must have description routines in a simulation. Finally, different types of stimulus sets may be organized differently in terms of different types of logical connectives. Sometimes involves joint presence of two or more characteristics. Such concepts are referred to as conjunctive concepts (e.g. large red figure). Other concepts involve presence of different subsets of characteristics. These are disjunctive concepts, e.g. red or large figures. Different ways of defining form of an answer are provided by a set of solution routines.The program must be capable of simulating a variety of conditions under which experiments have been performed. As illustrations of some of variations, or manipulations, which must be simulated following may be mentioned.The number and complexity of stimuli may vary from study to study. The speed of presentation of new stimuli can be altered. The instances may be left in view or subject may be forced to rely on his memory. Different learning problems can be compared along such dimensions as: logical complexity of correct answer, number of relevant vs. number of irrelevant dimensions, order of presentation of problems of different types, and presentation of information by positive or negative instances.The subject may make a variety of responses during experiment. Subjects may describe, verbally, their intermediate and final hypotheses concerning characteristics of concept. These responses may give us clues as to nature of individual's information processing procedures. As such, they constitute accessory measures used in our simulation studies. The time taken to develop an answer under various experimental conditions is also a useful response measure. The errors that subjects make in subsequent identifications of stimulus names can be analyzed. The more objective records are to be preferred, and our major goal is to predict these by computer simulation.In order to develop a theoretical explanation of learning we have accepted black box analogy. We have attempted to write a computer program which, when given as input coded representations of stimuli, will give as output coded responses that can be used to predict responses of a human subject. Accurate prediction of responses, not development of a good hypothesis developer, nor, solely, reproduction of previously obtained protocols, is our goal. We are not concerned with processes specific to task of categorizing geometric patterns. These are used as stimuli because they are convenient and because they represent stimuli which can be described in terms of previously discriminated stimuli. Hopefully we shall be able to make conclusions about learning processes irrespective of particular form of stimuli.Reports of our psychological experimental work have been, and are being, made in separate publications. This paper will be concerned with programming details of our learning model. This model has been completed, debugged, and used to simulate several experiments. After describing model we shall indicate result of some simulations and discuss modifications of model which have been indicated.The learning program is a list processing language program written for IBM 709-7090 data processing systems. The original programs were written in Information Processing Language V (IPL-V), interpreter list processing language developed by Newell, Simon, and Shaw (cf. Green). Partly for local administrative reasons, we are in process of converting our programs to LISP, a list processing language developed by McCarthy. We do not have sufficient experience with LISP to compare two languages for our type of problem. As basic logic of LISP and IPL-V programs are same no distinction will be made between them.