Mozetic, I., 1992, A polynomial-time algorithm for model-based diagnosis. In Proceedings, 10th European Conference on Artificial Intelligence, 729--733. Home/Search Document Details and Download
Summary Related Articles Check |
This paper is cited in the following contexts:
Explaining by Evidence - Lozinskii (Correct)
....that is, a process of finding reasons, causes and explanations of various events. Introduced by Peirce [5] abduction underlies numerous processes of a great practical importance, such as medical diagnosing [2, 20, 57, 62, 68, 70, 83] testing and repairing technical devices and structures [4, 11, 13, 21, 24, 40, 55, 58, 72], planning a course of action [7, 18, 59] natural language understanding [32, 33, 43, 44, 39, 74, 75] learning [14, 61, 74, 75] Let S denote a Knowledge System (presented in the language of First Order Logic) that describes a part of a real world W . Suppose that a state Obs has been observed ....
....with regard to the notion of explanation. What accounts for an explanation What determines the quality of an explanation What is a best explanation What is a process of inference to the best explanation [48] Numerous works on abduction adopt the following general definition of explanation [18, 19, 46, 58, 59, 66, 76]. 1 Definition 1.1 Given a system S, and an observation Obs, an explanation of Obs in S is a formula expl(S; Obs) that satisfies the following conditions: i) S [ fexpl(S; Obs)g j= Obs; ii) expl(S; Obs) is consistent with S. Usually several refinements of this definition are considered. 1) ....
[Article contains additional citation context not shown here]
Mozetic, I., 1992, A polynomial-time algorithm for model-based diagnosis. In Proceedings, 10th European Conference on Artificial Intelligence, 729--733.
Model-Based Diagnosis: An Overview - Mozetic (1992) (3 citations) Self-citation (Mozetic) (Correct)
....tuple where all components are ok. Reiter s algorithm [1987] for example, searches the lattice bottom up (from conflicts to diagnoses) in a breadth first fashion (diagnoses of smaller cardinality are found first) and relies on the underlying ATMS like theorem prover. In contrast, our algorithm [Mozeti c, 1992] better fits into the logic programming environment, and implements a top down, depth first search through the lattice. In diagnosing real systems, the search lattice is large and minimal diagnoses are usually near the bottom of the lattice. Depth first search, coupled with non ground model calls, ....
....time [Bakker et al. 1989] One solution to the complexity problem is to compute just some minimal diagnoses. De Kleer [1991] presents a focusing mechanism which enables efficient computation of a few most probable diagnoses. A polynomial algorithm for computing the first k diagnoses is in [Mozeti c, 1992] . Another solution is to compute just one minimal diagnosis, and to interleave diagnosis and treatment [Friedrich et al. 1990b] Finally, complexity can be reduced by introducing abstractions [Gallanti et al. 1989, Mozetic, 1990, Mozetic, 1991] 5 Abstractions and model compilation One ....
Mozetic, I. A polynomial-time algorithm for model-based diagnosis. Proc. European Conf. on Artificial Intelligence, ECAI-92, Vienna, Austria, 1992.
Computing Minimal Diagnoses with Critical Set Algorithms - Igor Mozetic Self-citation (Mozetic) (Correct)
....diagnosis. Our experiments indicate that the time to compute minimal diagnoses is dominated by the calls to the model of the device being diagnosed. In the paper we describe an attempt to reduce the number of model calls by incorporating two critical set al..gorithms [ Loveland, 1987 ] into IDA [ Mozetic, 1992 ] A critical set al..gorithm computes a minimal diagnosis with O(log n) model calls as opposed to O(n) model calls made by a straightforward algorithm. We performed experiments on two non trivial domains: a) a 1000 bit adder which has simple structure and behaviour, but large number of ....
....in polynomial time. Friedrich et al. 1990] give an algorithm to compute a single minimal diagnosis with a weak fault model in polynomial time. However, they show that, due to the set operations performed during the lattice search, finding the next minimal diagnosis is an NP complete problem. [Mozeti c, 1992] gives an improved incremental algorithm IDA which computes k minimal diagnoses in polynomial time. With a strong fault model (when abnormal behaviour is also specified) even computing the first (non minimal) diagnosis is NP complete [Bylander et al. 1989] In practice, the exponential growth ....
[Article contains additional citation context not shown here]
Mozetic, I. A polynomial-time algorithm for model-based diagnosis. Proc. 10th European Conf. on Artificial Intelligence, ECAI-92, pp. 729-733, Vienna, Austria, John Wiley & Sons, 1992.
Diagnosing Tree-Decomposable Circuits - Fattah, Dechter (1995) (12 citations) (Correct)
No context found.
I. Mozetic. A polynomial-time algorithm for modelbased diagnosis. In B. Neumann, editor, Proceeding of the 10th European Conference on Artificial Intelligence (ECAI 92), pages 729--733, New York, 1992. John Wiley & Sons.
Online articles have much greater impact More about CiteSeer.IST Add search form to your site Submit documents Feedback
CiteSeer.IST - Copyright Penn State and NEC