NDLI: Break of Logic Symmetry by Self-conflicting Agents: Descriptive vs. Prescriptive Rules

Content Provider	IEEE Xplore Digital Library
Author	Kovalerchuk, B. Resconi, G.
Copyright Year	2007
Description	Author affiliation: Dept. of Comput. Sci., Central Washington Univ. (Kovalerchuk, B.)
Abstract	Classical axiomatic uncertainty theories (probability theory and others) model reasoning of rational agents. These theories are prescriptive, i.e., prescribe how a rational agent should reason about uncertainties. In particular, it is prescribed that (1) uncertainty P of any sentencep is evaluated by a single scalar P(p) value, (2) the truth-value of any tautology (por-p) is true, and (3) the truth-value of any contradiction (pnland-p) is false for every proposition p. However, real agents can be quite irrational in many aspects and do not follow rational prescriptions. In this paper, we build a logic of irrational and conflicting agents called I-agent logic of uncertainty (IALU) as a vector logic of evaluations of sentences. This logic does not prescribe rules on how an agent should reason rationally, but describe rules on how agents reason irrationally. This is a descriptive not prescriptive theory in contrast with the classical logic and the probability theories. This provides a new possibility to better understand and model uncertainties associated with social conflict phenomena. We show that the fuzzy logic has a potential to become a scalar version of a descriptive logic of irrational agents because it satisfies several necessary conditions of IALU
Starting Page	348
Ending Page	353
File Size	5925906
Page Count	6
File Format	PDF
ISBN	1424409446
DOI	10.1109/KIMAS.2007.369834
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-04-30
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fuzzy logic Computer science Uncertainty Fuses Probabilistic logic Mathematics Probability distribution Mathematical model Physics
Content Type	Text
Resource Type	Article

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