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A maximum entropy approach to nonmonotonic reasoning

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TLDR
This paper provides a precise formalization of the consequences entailed by a defeasible knowledge base, develops the computational machinery necessary for deriving these consequences, and compares the behavior of the maximum entropy approach to those of Ɛ-semantics and rational closure.
Abstract
An approach to nonmonotonic reasoning that combines the principle of infinitesimal probabilities with that of maximum entropy, thus extending the inferential power of the probabilistic interpretation of defaults, is proposed. A precise formalization of the consequences entailed by a conditional knowledge base is provided, the computational machinery necessary for drawing these consequences is developed, and the behavior of the maximum entropy approach is compared to related work in default reasoning. The resulting formalism offers a compromise between two extremes: the cautious approach based on the conditional interpretations of defaults and the bold approach based on minimizing abnormalities. >

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Citations
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Proceedings Article

Inconsistency management and prioritized syntax-based entailment

TL;DR: This new approach leads to a nonmonotonic inference which satisfies the "rationality" property while solving the problem of blocking of property inheritance and differs from and improves previous equivalent approaches such as Gardenfors and Makinson's expectation-based inference, Pearl's System Z and possibilistic logic.
Book ChapterDOI

Toward a Logic for Qualitative Decision Theory

TL;DR: A logical calculus is developed that employs the basic elements of classical decision theory, namely probabilities, utilities and actions, but exploits qualitative information about these elements directly for the derivation of goals.
Journal ArticleDOI

Qualitative probabilities for default reasoning, belief revision, and causal modeling

TL;DR: A formalism that combines useful properties of both logic and probabilities and provides symbolic machinery for deriving deductively closed beliefs and permits us to express if-then rules with different levels of firmness and to retract beliefs in response to changing observations is presented.
Journal ArticleDOI

Expressive probabilistic description logics

TL;DR: This paper presents sound and complete algorithms for the main reasoning problems in the new probabilistic description logics, which are based on reductions to reasoning in their classical counterparts, and to solving linear optimization problems.
References
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Book

Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference

TL;DR: Probabilistic Reasoning in Intelligent Systems as mentioned in this paper is a complete and accessible account of the theoretical foundations and computational methods that underlie plausible reasoning under uncertainty, and provides a coherent explication of probability as a language for reasoning with partial belief.
Journal ArticleDOI

A logic for default reasoning

TL;DR: This paper proposes a logic for default reasoning, develops a complete proof theory and shows how to interface it with a top down resolution theorem prover, and provides criteria under which the revision of derived beliefs must be effected.
Journal ArticleDOI

A theory of diagnosis from first principles

TL;DR: The theory accommodates diagnostic reasoning in a wide variety of practical settings, including digital and analogue circuits, medicine, and database updates, and reveals close connections between diagnostic reasoning and nonmonotonic reasoning.
Journal ArticleDOI

Circumscription—A form of non-monotonic reasoning

TL;DR: The authors formalizes such conjectural reasoning and shows that the objects they can determine to have certain properties or relations are the only objects that do, which is a common assumption in human and intelligent computer programs.
Journal ArticleDOI

Nonmonotonic reasoning, preferential models and cumulative logics

TL;DR: In this paper, a number of families of nonmonotonic consequence relations, defined in the style of Gentzen [13], are studied from both proof-theoretic and semantic points of view.