Sage Journals: Discover world-class research

Abstract

The main purpose of the present work is to present and discuss a model for a decision maker who is using feedback information and is subjected to goal uncertainty. The decision maker is allowed to choose one of a finite number of courses of action and observe one of a finite number of possible outcomes resulting from his choice.

Two alternatives are available to 'learn' the best course of action. One is to assign a subjective score to each course of action, outcome pair and follow the courses of action that lead to the highest current estimates of the expected score. This approach quickly establishes a dominant course of action which under certain circumstances may not be optimal. The other alternative forces much more switching between courses of action and no dominant action arises.

These alternatives are combined in a two-phase approach to zeroing in on the optimal course of action. In phase one the decision maker cycles until enough information has accu mulated. In phase two he follows the highest expected utilities. The algonthm is written out in detail in the appendix.

Get full access to this article

View all access options for this article.

References

R. Alo , R. Kleyle and A. de Korvin , 'Decision making and stopping times in a generalized information system, Math. Modelling 6 ( 1985) 259-271.

R. Alo , R. Kleyle and A. de Korvin , Some dynamical properties of sequentially acquired information, Math Modelling 6 ( 1985 ) 339-351.

R. Aumann , Existence of competitive equilibria in markets with a continuum of traders, Econometrica 34 (1966) 1-17.

G. Debreu , Integration of correspondences, Proc. Fifth Berkeley Symp. on Math. Stat. and Prob, Vol. II, Part I, ( 1966 ) 351-372.

J. Doob , Stochastic Processes (Wiley, New York, 1953).

F. Hiai and H. Umegaki , Integrals, conditional expectations and martingales of multivalued functions , J. Multi-variate Analysis. 7 (1977) 149-182

D. Kahneman and A. Tversky. The psychology of preferences , Scientific American 246 (1982 ) 160-175.

R. Kleyle and A. de Korvin , Switching mechanisms in a generalized information system, Cybernetics and Systems 15 ( 1984) 145-167.

R. Kleyle and A. de Korvin , Martingale properties of an information feedback loop submitted for publication.

10.

A. de Korvin and R. Kleyle , Goal uncertainty in a generalized information system: convergence properties of the estimated expected utilities , Stochastic Analysis and Applications 2 (1984) 437-457.

11.

A. de Korvin and R. Kleyle. Emergence of a dominant course of action in a general feedback loop when goal uncertainty is present, submitted for publication.

12.

A. de Korvin and R. Kieyle , Goal uncertainty and the supermartingale property in an information feedback loop, submitted for publication

13.

A. de Korvin and R. Kleyle , A convergence theorem for convex set valued supermartingales Stochastic Analysis and Applications, to appear.

14.

F.S. Scalora , Abstract martingale convergence theorems , Pac. J. Math. 11 ( 1961) 347-374.

15.

M.C. Yovits , C.R. Foulk and L.L. Rose , Information flow and analysis: theory, simulation and experiment. Part I. Basic theoretical and conceptual development , Journal American Soc Information Science 32 (1981) 187-202.

16.

M.C. Yovits , C.R. Foulk and L.L. Rose , Information flow and analysis: theory. simulation and experiment. Part II. Simulation; examples and results, Journal American Soc. Information Science 33 (1981) 203-210.

17.

M.C. Yovits and C.R. Foulk , Expectations and analysis of information, use and value in a decision-making context, Journal American Soc Information Science 36 ( 1985) 63-81.

A two-phase approach to making decisions involving goal uncertainty

Abstract

Get full access to this article

References