Skip to main content

An Information processing theory of human decision making under uncertainty and risk


Computer-based experiments were made to observe and record the verbal behavior of subjects making decisions in quantitative task environments under uncertainty and risk. The subjects exhibited different categories of mental representation of the task environment. These representations form the basis of their search and optimizing techniques.

The second phase of the project consisted of generating a psychological theory of the above behavior, in the form of a computer program. Comparing the trace of the program with tape-recorded protocols may indicate the level of completeness of the theory. It was found that the information processing approach can successfully explain general characteristics of decision making behavior and also some individual idiosyncrasies.

This is a preview of subscription content, access via your institution.


  1. [1]

    A “rational” person is (a) completely informed, (b) infinitely sensitive and (c) can formulate his problem in an optimum manner.

  2. [2]

    The interested reader's attention is drawn to the following, far from exhaustive list of papers and books, and to the extensive bibliographies included in them: Hart, A. G.: Risk, uncertainty and the unprofitability of compounding probabilities. In: O. Lange, F. McIntyre and T. O. Yntema (eds.), Studies in mathematical economics and econometrics. Chicago: Chicago University Press 1942. Wald, A.: Statistical decision functions. New York: Wiley 1950. Edwards, W.: The theory of decision making. Psych. Bull. 51, 380–417 (1954). Thrall, R. M., C. H. Coombs, and R. L. Davis (eds.): Decision processes. New York: Wiley 1954. Blackwell, D., and M. A. Girschik: Theory of games and statistical decisions. New York: Wiley 1954. Wasserman, P., and F. S. Silander: Decision making, an annotated bibliography. Grad. School of Business and Public Administration, Cornell Univ., 1958. Luce, R. D., and H. Raiffa: Games and decisions, introduction and critical survey. New York: Wiley 1958. Weiss L.: Statistical decision theory. New York: McGraw-Hill Book Co. 1961. Machol, R. E., and P. Gray (eds.): Recent developments in information and decision processes. New York: Macmillan 1962.

    Google Scholar 

  3. [3]

    The basic philosophy of this approach is described in detail, e.g. in A. Newell and H. A. Simon, Computers in psychology. In: Luce, Bush and Galanter (eds.), Handbook of mathematical psychology, vol. I. New York: Wiley 1963.

    Google Scholar 

  4. [4]

    Simon, H. A., and A. Newell: Information processing in computer and man. CIP Paper No. 67, Carnegie Institute of Technology, March 31, 1964.

  5. [5]

    Newell, A., J. C. Shaw, and H. A. Simon: Chess-playing programs and problem of complexity. IBM J. Res. and Dev. 2, 320–335 (1958).

    Google Scholar 

  6. [6]

    Newell, A., J. C. Shaw, and H. A. Simon: Empirical explorations of the logic theory machine. Proc. WJCC, Los Angeles, Calif., pp. 218–230, (1957).

  7. [7]

    Gelernter, H.: Realization of a geometry-theorem proving machine. Proc. Internat. Conf. on Information Processing, Paris, pp. 273–282, 1959.

  8. [8]

    Robinson, J.: Theorem-proving on the computer. J ACM 10, 163–174 (1963).

    Google Scholar 

  9. [9]

    Hunt, E. B., and C. I. Hovland: Programming a model of human concept formulation. Proc. WJCC, Los Angeles, Calif., pp. 145–155, 1961.

  10. [10]

    Feigenbaum, E. A.: The simulation of verbal learning behavior. In: Feigenbaum and Feldman (eds.), Computer on thought. New York: McGraw-Hill Book Co. 1963.

    Google Scholar 

  11. [11]

    Newell, A., and H. A. Simon: GPS, A program that simulates human thought. In: H. Billing (ed.), Lernende Automaten, pp. 109–124. Munich: Oldenbourg 1961.

    Google Scholar 

  12. [12]

    Feldman, J.: Simulation of behavior in the binary choice experiment. Proc. WJCC, pp. 133–166, Los Angeles, Calif. 1961.

  13. [13]

    Clarkson, G. P. E.: A model of the trust investment process. In: Feigenbaum and Feldman (eds.), Computer and thought. New York: McGraw-Hill Book Co. 1963.

    Google Scholar 

  14. [14]

    See e.g. Hull, C. L.: Principles of behavior. New York: Appleton-Century-Crofts 1943 or Bush, R. R., and W. K. Estes: Studies in mathematical learning theory. Stanford: Stanford University Press 1959.

    Google Scholar 

  15. [15]

    See e.g. Simon, H. A.: An information processing theory of intellectual development. In: W. Kessen and C. kuhlman (eds.), Thought in the young child. Monogr. Soc. Res. Child Dev. 27, 137–161 (1962).

  16. [16]

    See e.g. Simon, H. A.: A theory of emotional behavior. CIP Working Paper, No. 55. Carnegie Institute of Technology, June 1, 1963.

  17. [17]

    As one subject (of what sex ?) said: “I can see small particles swirling around in a big blue room, hitting each other and the walls. The faster they fly the higher values these C's take.”

  18. [18]

    Luchins, A. S.: Mechanization in problem solving: The effect of Einstellung. Psych. Monographs 54, No. 6; Whole No. 248, pp. 1–95 (1942).

    Google Scholar 

  19. [19]

    Garner,w. R.: Uncertainty and structure as psychological concepts. New York: Wiley 1962.

    Google Scholar 

  20. [20]

    Hooke, R., and T. A. Jeeves: “Direct Search” solution of numerical and statistical problems. J ACM 8, 212–229 (1961).

    Google Scholar 

  21. [21]

    Flood, M. M.: Stochastic learning theory applied to choice experiments with rats, dogs and men. Behav. Sci. 7, 289–314 (1962).

    Google Scholar 

  22. [22]

    One subject, disregarding the fact that there were three independent variables instead of two, considered the environment as some terrain and the C values representing the height of mountains, hills, and valleys. His “hill-climbing” was a tourist's excursion.

  23. [23]

    Compare the “strategies of decision making” as described by J. S. Bruner, J. J. Goodnow and G. A. Austin, in: A study of thinking (New York: Wiley 1956) or the TOTE units by G. A. Miller, E. Galanter and K. H. Pribram, in: Plans and structure of behavior (New York: Holt 1960).

    Google Scholar 

  24. [24]

    One must not become confused by the directions of change: the aspiration level increases if a better, i.e. lower, C value has been found, and vice versa.

Download references

Author information



Additional information

This terminology is not quite uniform. Most authors in Statistical Decision Theory and Economics have adopted the convention that in a situation of uncertainty there is no à priori information about the system at hand, consequently probability distributions of various alternative outcomes cannot be objectively specified. In cases involving risk, however, it is assumed that, relying on prior events of identical character, these frequency distributions are available. In the present work we have not distinguished between these two cases and Described the psychological state of the subjects as that under uncertainty. The element of risk is represented by the subjects' financial involvement in the outcome of the experiments. The adopted terminology and the distinction made here may be rather useful with experiments which aim at discovering correlation between subjects' behavior and varying pay-off matrices while the stochastic components of the environment stay stationary.

The work reported here was done at Carnegie Institute of Technology and was supported by the Advanced Research Projects Agency of the Office of the Secretory of Defense: Contract SD-146.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Findler, N.V. An Information processing theory of human decision making under uncertainty and risk. Kybernetik 3, 82–93 (1966).

Download citation


  • Decision Making
  • Information Processing
  • Computer Program
  • General Characteristic
  • Mental Representation