By Christian Straßer

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

The writer first familiarizes readers with defeasible reasoning, the adaptive logics framework, mixtures of adaptive logics, and quite a number valuable meta-theoretic houses. He then deals a scientific learn of adaptive logics in response to a variety of functions.

The ebook offers formal versions for defeasible reasoning stemming from assorted contexts, comparable to default reasoning, argumentation, and normative reasoning. It highlights numerous meta-theoretic benefits of adaptive logics over different logics or logical frameworks that version defeasible reasoning. during this method the ebook substantiates the prestige of adaptive logics as a popular formal framework for defeasible reasoning.

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

Example text

B 5,10; RU ∅ Note that c at line 6 is reinstated in view of the new evidence. b at line 11. Again, looking at the sequence P1 , P2 , P3 we see a detailed explication of the dynamics of her reasoning process: in P1 we see the rationale behind accepting the inference at line 6 as finally derived since the condition was reliable (meaning it only contained reliable abnormalities), in P2 the inference was retracted since the condition contained an unreliable abnormality, finally in P3 the inference is safe again since the condition is reliable again.

F. e. LLL F and LLL ¬ By Ω we denote the set of all formulas of the form F. For our application (i) abnormalities may have the form of inconsistencies, A ∧¬ A. For application (ii) abnormalities may have the form of deontic conflicts, O A ∧ O¬A. To interpret the premises “as normally as possible” means to interpret the premises in such a way that as few abnormalities as possible are validated. We will see that semantically ALs select LLL-models of a given premise set that are “sufficiently normal” in terms of the abnormalities they validate.

N} PREM ∅ 4,5,8; RU ∅ 32 2 The Standard Format for Adaptive Logics The new information causes the marking of lines 6 and 7: while c was a consequence from Γ1 it ceases to be a consequence given the new information ¬a ∨ ¬b. Reusing and extending the proof P1 resulting in P2 explicates the reasoning process that leads to the retraction of the previous inferences resulting in c: hence it provides an understanding as to why our detective previously inferred c (given only Γ1 ) and then she gave up on it (given Γ2 ).