Abstract
A logic can be formulated with information systems as elements. The calculus of this logic is similar to, but not identical with, Boolean algebra. The logic is inductive—conclusions have more information than premises. Inferences have a strong justification; they are valid for all proper scoring rules.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Birkhoff, G. (1940). Lattice Theory. American Mathematical Society (Colloquium Publications, 25), New York.
Dalkey, N.C. (1980). The Aggregation of Probability Estimates. UCLA-ENG-CSL-802S.
Dalkey, N.C. (1985). Inductive Logic and the Maximum Entropy Principle. In Maximum Entropy and Bayesian Methods in Inverse Problems, eds. C. Ray Smith & W.T. Grundy. Boston: D. Reidel Publishing Co.
Dalkey, N.C. (1987). Information Systems. UCLA-ENG-CSL Report, in preparation.
LaValle,. (1978). Fundamentals of Decision Analysis. New York: Rhinehart & Winston.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1988 Kluwer Academic Publishers
About this chapter
Cite this chapter
Dalkey, N.C. (1988). A Logic of Information Systems. In: Erickson, G.J., Smith, C.R. (eds) Maximum-Entropy and Bayesian Methods in Science and Engineering. Fundamental Theories of Physics, vol 31-32. Springer, Dordrecht. https://doi.org/10.1007/978-94-009-3049-0_16
Download citation
DOI: https://doi.org/10.1007/978-94-009-3049-0_16
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-010-7871-9
Online ISBN: 978-94-009-3049-0
eBook Packages: Springer Book Archive