Download Adaptive Logics for Defeasible Reasoning: Applications in by Christian Straßer PDF

By Christian Straßer

ISBN-10: 3319007912

ISBN-13: 9783319007915

This publication offers adaptive logics as an intuitive and robust framework for modeling defeasible reasoning. It examines a number of contexts within which defeasible reasoning turns out to be useful and provides a compact creation into adaptive logics.

The writer first familiarizes readers with defeasible reasoning, the adaptive logics framework, mixtures of adaptive logics, and a number invaluable meta-theoretic homes. He then deals a scientific learn of adaptive logics according to quite a few functions.

The booklet provides formal versions for defeasible reasoning stemming from various contexts, equivalent to default reasoning, argumentation, and normative reasoning. It highlights a variety of meta-theoretic merits of adaptive logics over different logics or logical frameworks that version defeasible reasoning. during this means the ebook substantiates the prestige of adaptive logics as a commonplace formal framework for defeasible reasoning.

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Additional info for Adaptive Logics for Defeasible Reasoning: Applications in Argumentation, Normative Reasoning and Default Reasoning

Example text

Let henceforth CL◦ r be the AL defined by the triple: 5 I do of course not claim that the modeling of the defeasible reasoning of our detective by CL◦ is by any means optimal. It is however sufficiently intuitive and simple in order to serve as a toy application for introducing the basic concepts and mechanisms of ALs. 16 2 The Standard Format for Adaptive Logics 1. lower limit logic: CL◦ 2. abnormalities: Ω◦ 3. 1 The Semantics Let us first take a look at the semantics. What CL◦ -models of the premise set Γ1 = {◦n, (a ∧ n) ⊃ c, (b ∧ n) ⊃ c, ◦a, ◦b, ¬a ∨ ¬b} should be selected according to the cautious rationale of our detective?

M3 validates both of them. Note that in the model M3 , c is not validated. After all, the interpretation offered by M3 treats both a and b as unreliable and thus in this interpretation neither (a ∧ n) ⊃ c nor (b ∧ n) ⊃ c can be used for deriving c. Hence, our cautious detective does not (tentatively) conclude that Mr. X is the murderer. Generically the semantic consequence relation for the reliability strategy is defined as follows. 1. Where MALr (Γ ) is the set of all reliable LLL-models of Γ , Γ ALr A iff for all M ∈ MALr (Γ ) , M |= A.

Let us model the defeasible reasoning of a detective. Suppose a murder happened. There are two witnesses. One states that the major suspect Mr. X entered the scene of crime right before the lethal shot was heard throughout the whole neighborhood. Another one states that he saw the major suspect leaving the scene of crime directly after the shot was heard. Moreover, our detective has the information that nobody else was at the scene of crime shortly before and shortly after the time of the killing.

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