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COMPUTER SIMULATION OF HUMAN BEHAVIOR

E. A. Feigenbaum

May 1964'

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COMPUTER SIMULATION OF HUMAN BEHAVIOR

E. A. Feigenbaum

Consultant to The RAND Corporation, Santa Monica, California

Although the emphasis of this paper is human cognitivebehavior (learning and problem- solving processes), a fewremarks about the "simulator" of this behavior, the digitalcomputer, are in order.

Computers as Information Processors

Ordinarily, we think of the digital computer as a veryhigh-speed number manipulator- -a calculator. Certainly,the very term "computer" implies numerical calculation;and indeed, a computer is mainly used for just this purposelarge-scale numerical computation. But the symbols of thecomputer, the strings of bits it manipulates, do not neces-

sarily have to be assigned a numerical interpretation. We

can consider a particular string of bits as a binary numberand manipulate it by means of hardware that performs addi-tion, subtraction, etc. But we can also give other-than-numerical interpretations to these symbols. A digital com-

puter is a general information processing system, a general

*Any views expressed in this paper are those of theauthor. They should not be interpreted as reflecting theviews or opinions of The RAND Corporation or the officialopinion or policy of any of its governmental or privateresearch sponsors. Papers are reproduced by The RANDCorporation as a courtesy to members of its staff.

This paper is based on a survey lecture givenperiodically by the author to interested audiences.

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symbol manipulating device, quite apart from its use asa calculator. It is capable of carrying out any_ well-

defined, precisely stated process for the manipulation of

information.

Human Information Processing

In the last fifteen years, psychologists have shown

a great deal of interest in the information processing

capabilities of the human being—for example, how the

human stores information, how he responds to information,

what his various reaction times are. A large share of

this interest in human information processing has come

about because of the need for studies of the human factors

involved in the integration of people into large man-

machine systems, especially where the machines are informa-

tion processing machines. The amount of this research has

so increased in magnitude that now it occupies a signifi-cant proportion of each issue of the Journal of Experimental

Psychology. Concomitant with the experimental psycholo-

gists' broad interest in human information processing,there has been a growth of interest in constructing theories

of human information processing abilities.

Information Processing Theory and Computer Simulation

The goal of this work is the construction of valid

information processing theories of human mental function.

Note that the stress is on mental function, on cognitiveactivity, rather than on physiological activity, although

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there is much work being done on modeling of physiologicalprocesses of the brain. However, the focus in this dis-cussion is on the attempt to model processes of humaninformation processing at the psychological level. Thecomputer is used as an information processing tool forworking out the remote consequences (or implications) ofa complex set of information processing hypotheses. Inthe particular research to be described, no comparisonsare made between computer organization and neural organi-zation at the level of hardware (or "wetware," if you will)although in the popular press one often finds comparisonsof this kind, the comparisons are usually completely wrongand misleading, and are rarely made by competent researchpeople in the field.

On a level of integration above the level of eithercomputer organization or neural organization, we postulatea level of elementary information processing, or elementarysymbol manipulation. This is the so-called informationprocessing level of constructing theories of cognitiveprocesses. This is a very gross and macroscopic levelof processing compared with processing at the level ofneural firings. Elementary symbol manipulations deal,for example, with storage of symbols, comparisons of two

symbols, decision-making action based on the presence or

absence of some symbol, etc. These elementary informationprocesses are organized as programs and information struc-

tures which, it is hypothesized, are models of processesand structures used by the human mechanism. The processesand structures form a closed model, capable of being "run"

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in a computer. We use this closed model as a subject in

simulated psychological experiments.A stream of behavior emerges from the computer simu-

lation. This is the model's prediction for the experiment

simulated. From experiments with humans we have a stream

of observed behavior; i.e., behavior that has been evoked

when we have put subjects through the same laboratory

experiments as those simulated. The human behavior and

the model's behavior are compared for purposes of valida-

tion of the model. If the model is adequate there will

be a great deal of similarity between the two streams of

behavior. If there are important differences, an attempt

is made to discover what is wrong or missing in the model.

Often this loop must be traversed many times before a

model is developed in which confidence can be placed.

To accomplish these modeling tasks, powerful informa-

tion processing computer languages are needed, and some

have been developed. Perhaps the best known of these is

IPL-V, the language in which most of the work on the

simulation of cognitive processes has been done. Two

different types of simulation models have been, and are

being, constructed.

Computer Simulation Within Existing Frameworks

On the one hand, some investigators have been inter-

ested in casting already- existing theories into an informa

tion processing framework to test the sufficiency and the

implications of these theories. For example, a theory of

neural cell assemblies was tested at the IBM Research

Center, by Rochester, Holland, Haibt, and Duda, around

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(2)1956. Colby at Stanford University is attempting to

restate psychoanalytic constructs in information proces-sing terms, defining these constructs in terms of informa-tion transformations on both external messages put intothe system and internal beliefs held by the system. J

(For example, the standard psychoanalytic construct of"projection" might be thought of as an information trans-

formation which changes a belief, "I hate father," to

the belief "He hates father.") Finally, Gullahorn andGullahorn of Michigan State University have augmented

and simulated a model of multi-person interaction originally(4)

suggested by Homans. The model deals with the inter -changes observed in a small-group situation in which peopleare talking to each other and attempting to influence eachother in various ways. The Gullahorns have found a numberof statements in the Homans' system that had to be modified

and a number of additions that had to be made in order to

make the model sufficient and complete—so that it would

actually operate in simulation.

■kOne of the advantages of computer simulation is that

of guaranteeing sufficiency and completeness of a theory.If one fails to take into account some necessary mechanismthat, in the verbal description of a theory, one. mightreadily pass over, the computer simulation will not run.Thus, one is forced to focus attention on all the mech-anisms—those that are not well understood in additionto those that are well understood--and all the subtleeffects and interactions which are implicit in one's model.In a sense, accounting for all the information processingis a very powerful mental discipline. It is analogous toenergy analysis in physics. In studying a complex physicalinteraction, it is incumbent upon the scientist to accountfor all the energy that goes into and comes out of theinteraction. Similarly, in the simulation discipline,the model builder must account for all steps in the informa-tion processing.

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New Information Processing Models

The second class of models that have been constructed

comprises new and different models of cognitive processes-

models not previously proposed in some other form. For ex-

ample, one such model is of human verbal learning processes,(5)

worked out by the author and Professor H. A. Simon.

It is a model of the acquisition of verbal material by

subjects in verbal learning experiments; e.g., acquisition

of nonsense syllables in serial list and paired-associate

presentations. This model can be exercised in rote learn-

ing experiments of many different kinds, some standardand some not so standard.

The hypotheses which comprise the model are realized

as programs for performance in a verbal learning situation

(e.g., responding to a particular stimulus, recognizing

particular stimuli), and forthe discrimination among the

learning task; familiarizing

matching memorized images to

learning (e.g., acquiringdifferent items ia a verbaland integrating the items;

detect differences between

them; associating memorized images of the external stimuli

with each other so that the presentation of one will cause

the evocation of the other associatively) .This model, called EPAM for Elementary Perceiver and

Memorizer, has been programmed in IPL-V. It consists

of some 2000 instructions in this computer language. EPAM

has been run in about 200 simulations of various kinds of

verbal learning experiments. Many of the well-known and

stable phenomena of rote learning in serial and paired-

associate learning experiments are predicted by this model.

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Some of these are quantitative predictions as, for ex-

ample, the shape of the serial position curve in

learning (the fact that subjects learn end items beforemiddle items in a serial list leads to a characteristicbowed error curve which is very stable) . The model alsogives some qualitative predictions for certain phenomenaof verbal learning which have never been fully quantifiedin psychological literature but have been noted as im-

portant in verbal learning. For example, EPAM makesqualitative predictions of the effects that different

kinds of stimuli have on the production of various types

of errors in the subject's behavior; the kinds of intrusionerrors the subject will make; "oscillation" of correct

responses once learned, then unlearned, then learned againin the course of the learning of a single list. In total,

the EPAM model predicts, either quantitatively or quali-tatively, about a dozen of the most important stablephenomena of rote serial learning.

Many other individuals are actively working in computer

simulation of cognitive processes. Newell and Simon at

Carnegie Institute of Technology, for instance, are at-

tempting to construct a theory of human problem solving.Their theory receives its precise statement in a programcalled the General Problem Solver, or GPS. In very

general terms, Newell and Simon have been concerned withhow a problem solver builds and searches a hierarchy of

problem- solving goals and subgoals. They are concernedwith processes by means of which the problem solver dividesa complex task into simpler tasks, the answers to whichwill take him toward the total solution.

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The General Problem Solver uses two major methods

in its problem solution, based upon hypotheses about how

people organize problem- solving activity. The first method

is the so-called "means-ends analysis." In this method,

the problem solver works back and forth between ends that

need to be achieved and means (or operators) available for

achieving these ends. The second major method used by

GPS is that of planning. This concerns the question of

how to organize a problem- solving activity in advance, how

to achieve "good guesses" as to the path along which the

problem solving should proceed.Newell and Simon have done some detailed comparisons

of the "trace" of this computer simulation model with

human behavior in a "thinking-aloud" protocol which they

have taken from a number of subjects (in this case, students

at Carnegie Tech). A portion of one of these comparisons

is given in an article by Newell and Simon. The protocol

that they exhibit represents about five or ten minutes in

a complex problem- solving task. GPS is shown to simulate

almost exactly what the subject is doing--trying the same

problem (subproblems), making the same errors, coming back

to the same places, and going down the same blind alleys.

Another important and interesting model is the Binary

Choice Model of Julian Feldman at the University of

California.^ ' This is a model of human behavior in an

experiment with sequences of binary events. Feldman gives

his subjects a sequence of 200 binary events sometimes

patterned and sometimes not. The subject's job is to

guess the next event when he sees a particular event. Each

time the subject makes a guess as to what the next event

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is going to be, Feldman asks him the reason for his

choice. Here are examples of reasons given by subjects:

"You're going to give me u£ next time because you'vebeen giving me a run of ups" ; or, "The next one is going

to be down because the last one was u£ and you had been

giving me a run of downs and the last one was just to

throw me off." Feldman' s model is a model of how subjects

construct hypotheses about the sequence of events in this

binary series. The hypotheses constitute the reasonsgiven by the subject for his choices in this experiment.

Feldman fits the model to particular subjects' behavior,

using one sequence to set the parameters for the particu-lar subject and using a second sequence to validate the

model of the subject.

Another interesting computer simulation is that

done by E. B. Hunt. Hunt's model deals with behavior

in a standard concept- formation task. Subjects are pre-

sented exemplars and nonexemplars of a concept the ex-perimenter has in mind. After the learning phase is

over, subjects are asked to identify future presentationsas exemplars or nonexemplars of the concept. Hunt pro-

poses a mechanism that grows classification trees for

sorting new items to decide whether or not these items

fall into one category or another (i.e., whether they

are examples of a certain concept, or not).

R. Abelson of Yale University has developed a model

of the processes used by humans to assess the credibility

of statements prior to making the decisions to believe(9)

these statements. ' His program uses a large memory

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structure in which "things of the world" are categorized.

It consults this memory structure in a particular way to

decide whether a particular statement is explicable interms of what has been previously believed— i. e. , in terms

of what has been added to its memory structure. If it

can find a path of explication--! . e. , if it can find that

this new statement is explicable in terms of statements

already believed— it will assess this belief as credible;

if not, it will reject the statement. Sometimes, when

it has strong grounds for both believing and not believing

this statement, it will question whether or not the state-

ment is credible.G.P.E. Clarkson of the Massachusetts Institute of

Technology has developed a very careful model of human

decision-making in trust investment decision-makingsituations. Clarkson investigated the decision-making

behavior of a particular trust investment officer in a

bank in Pittsburgh, detailing how the man thought about

his investment problems. He asked him questions, observed

what the man was reading, asked for interpretations of

the reading, gave artificial problems to try to elicit

the man's problem- solving techniques and decision-making

heuristics, and so on. Clarkson then wrote a computer

simulation of the man's decision-making processes. In a

test of this model, done after the first quarter of the

following year, when the bank officer had four different

portfolios to select, Clarkson used his program to simulate

the selections, using up-to-date information on client,

amount, stock market, and so on. In all four cases, the

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predictions of the man's behavior were almost perfect.It is instructive, and rather startling, to study thecomparison charts given by Clarkson in his book, PortfolioSelection: A Simulation of Trust Investment. '

Simon and Kotovsky of Carnegie Tech have developeda theory of human acquisition of patterns in serial pattern

acquisition tasks (in particular, the Thurstone letter-and number-series completion tests, found on some intel-

(l2)ligence tests) . They have a program that constructs

a model of the sequence being presented, its periodicities,lags, etc. A pattern performance program uses this modelto generate forward the next elements in the sequence.They have shown the verisimilitude between the predictionof the pattern acquisition model and actual human datain series completion tests

(13)Finally, Crossman and Cooke in England have beenconstructing a computer model of human performance in a

manual control task. They wish to discover how peopleactually process information when they perform a complexmanual control sequence. They have been running an ex-

periment in which a subject has to control the temperatureof a chemical bath based on the settings of certain knobs.The question is: What knob- turning decisions will bemade by the subjects, and how can one model the under-lying information processes? Crossman and Cooke are justbeginning to construct a computer model of how peoplesearch for reasonable settings of these knobs in a simpleway.

In conclusion, I would like to emphasize a method-ological point. The central theme of all the research I

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have described is the information processing model, not

the computing machine. The computer simulation is usedas a means of realizing the information processing model

in a precise form, exactly as a physicist would realizehis theory formally in mathematical notation. Mathematics

is not a very convenient language in which to state these

information processing theories. Computer language is

convenient, not only because it is designed to handleinformation processing, but also because once a model is

expressed in this language, a computer is available as a

tireless tool for generating remote consequences of com-

plex sets of information processing hypotheses.

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REFERENCES

1. Newell, A., F. M. Tonge, E. A. Feigenbaum, B. F. Green,Jr., and G. H. Mealy, Information Processing Language-V Manual , 2nd cd. , Prentice-Hall, Inc., EnglewoodCliffs, New Jersey, 1964.

2. Rochester, N. , J. H. Holland, L. H. Haibt, and W. L.Duda, "Test on a Cell Assembly Theory of the Actionof the Brain, Using a Large Digital Computer," IRETrans. Info. Theory, IT- 2 (1956) 80-93.

3. Colby, X. , "Computer Simulation of a Neurotic Patient,'in Computer Simulation of Personality, Tompkins andMessick (eds.), Wiley, New York, 1963.

4. Gullahorn, John, and Jeanne Gullahorn, "A Model ofElementary Social Behavior," in Computers and Thought,E. A. Feigenbaum and J. Feldman (eds.), McGraw-Hill,New York, 1963.

5. Feigenbaum, E. A., "The Simulation of Verbal LearningBehavior," in Computers and Thought, E. A. Feigenbaumand J. Feldman (eds.), McGraw-Hill, New York, 1963.Also published in Proceedings of the Western JointComputer Conference (1961) , Institute of RadioEngineers, New York, 1961, pp. 121-132.

6. Newell, A., and H. A. Simon, "GPS, A Program thatSimulates Human Thought," in Computers and Thought,E. A. Feigenbaum and J. Feldman (eds.), McGraw-Hill,New York, 1963. Also published in Lernende Automaten,H. Billings (cd.), Oldenbourg, Munich, 1961.

7. Feldman, J., "Simulation of Behavior in the BinaryChoice Experiment," in Computers and Thought, E. A.Feigenbaum and J. Feldman (eds.), McGraw-Hill,New York, 1963. Also published in Proceedings ofthe Western Joint Computer Conference (1961) ,Institute of Radio Engineers, New York, 1961, pp.133-144.

8. Hunt, E. 8. , and C. I. Hovland, "Programming a Modelof Concept Formulation," in Computers and Thought,E. A. Feigenbaum and J. Feldman (eds.), McGraw-Hill,New York, 1963. Also published in Proceedings ofthe Western Joint Computer Conference (1961) ,Institute of Radio Engineers, New York, 1961,pp. 145-155.

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9 Abelson, R. , et al. , "A Computer Program which Assessesthe Credibility of Statements," Unpublished Manuscript,Department of Psychology, Yale University.

10 Clarkson, G.P.E., "A Model of the Trust Investment

and J. Feldman (eds.), McGraw-Hill, New York, 1963.11 , Portfolio Selection: A Simulation of Trust

New Jersey, 1962.12 Simon, H. A. , and K. Kotovsky, "Human Acquisition of

Concepts for Sequential Patterns," PsychologicalReview, 70 (1963) 534-546.

13 Crossman, E. , and J. Cooke (Institute for ExperimentalPsychology, Oxford), Private Communication.

Process," in Computers and Thought, E. A. Feigenbaum

Investment, Prentice-Hall, Inc., Englewood Cliffs,