Some of the issues in case retrieval and maintenance of case-bases are discussed. Conventionally, nearest neighbor algorithm is applied for retrieval of similar cases. Uniqueness of feature-values is not rewarded in s...
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ISBN:
(纸本)1577352343
Some of the issues in case retrieval and maintenance of case-bases are discussed. Conventionally, nearest neighbor algorithm is applied for retrieval of similar cases. Uniqueness of feature-values is not rewarded in such similarity matching functions. In order to refine the retrieval process, a metric based on successful case usage in the past is incorporated. This metric is shown to be useful in case-base maintenance. Applications in Homoeopathy remedy and personal tour selection are presented with comparative results.
We use assertions to reduce the quantity of queries in declarative diagnosis of logic programs. We first present a declarative diagnoser for normal logic programs. Given a bug symptom, the diagnoser first constructs a...
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ISBN:
(纸本)9781581139648
We use assertions to reduce the quantity of queries in declarative diagnosis of logic programs. We first present a declarative diagnoser for normal logic programs. Given a bug symptom, the diagnoser first constructs a tree that models the execution of the bug symptom and then searches the tree for the bug that causes the bug symptom. We then incorporate into the diagnoser three tree transformations that prune the tree before it is searched. These transformations make use of two kinds of assertion about the correctness of the program and maintain the soundness and completeness of the diagnoser. These transformations reduce the size of the tree and thus reduce the quantity of queries imposed on the oracle. Copyright 2005 ACM.
In this paper we present CurryBrowser, a generic analysis environment for the declarative multi-paradigm language Curry. CurryBrowser supports browsing through the implementation of an application written in Curry, i....
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Attack graphs represent known attack sequences that attackers can use to penetrate computer networks. Recently, many researchers have proposed techniques for automatically generating attack graphs for a given computer...
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Using SAT solvers as inference engines in answer set programming systems showed to be a promising approach in building efficient systems. Nowadays SAT based answer set programming systems successfully work with nondis...
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Using SAT solvers as inference engines in answer set programming systems showed to be a promising approach in building efficient systems. Nowadays SAT based answer set programming systems successfully work with nondis-junctive programs. This paper proposes a way to use SAT solvers for finding answer sets for disjunctive logic programs. We implement two different ways of SAT solver invocation used in nondisjunctive answer set programming. The algorithms are based on the definition of completion for disjunctive programs and the extension of loop formula to the disjunctive case. We propose the necessary modifications to the algorithms known for nondisjunctive programs in order to adapt them to the disjunctive case and demonstrate their implementation based on system CMODELS.
logic is a universal language of abstract concepts of two-valued world. Fuzzy logic is a cornerstone of abstraction of real (continuous) world. Granular Computing is aimed at the development, processing and exchanging...
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ISBN:
(纸本)0769522912
logic is a universal language of abstract concepts of two-valued world. Fuzzy logic is a cornerstone of abstraction of real (continuous) world. Granular Computing is aimed at the development, processing and exchanging information granules. Viewing such granules as abstractions of real world, their manipulation is ultimately governed by the mechanisms of logic, and fuzzy logic in particular. In this talk, we focus on a general platform of granular modeling - a paradigm that seamlessly combines the concepts of information granules with their logic processing cast in the operational framework of fuzzy sets. First, we outline the research agenda of granular modeling. Second, we elaborate on the architectural and algorithmic issues of granular models. The talk offers a systematic view at the development of information granules (realized as fuzzy sets and fuzzy relations) through descriptive, prescriptive, and hybrid approaches. Those approaches arise under the rubric of clustering and knowledge-based clustering. The processing core handling processing information granules involves a spectrum of logic constructs. Those include OR, AND, OR/AND fuzzy neurons. In conjunction to their basic logic characteristics articulated by means of "standard" logic operators (being realized via some t-and s-norms), we show how their underlying functionality could be augmented through more advanced constructs such as cardinal sums and uninorms. We discuss several categories of processing units aimed at referential processing supported by matching, inclusion, dominance, and difference fuzzy neurons. In the sequel, we present fundamental topologies of logic networks including logic processors, fuzzy multiplexers, and referential processing units. The issue of transparency-accuracy tradeoffs of granular models is presented along with various mechanisms of pruning logic networks and their underlying quantification aspects (articulated in the sense of the approximation error and being viewed vi
Programmers need mechanisms to store application specific data that persists multiple program runs. To accomplish this task, they usually have to deal with storage specific code to access files or relational databases...
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The Rewriting-calculus (Rho-calculus), is a minimal framework embedding Lambda-calculus and Term Rewriting Systems, by allowing abstraction on variables and patterns. The Rho-calculus fea- tures higher-order functions...
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We introduce the consistent topological structure and neighborhood structure into the logical framework for providing the logical foundation and logical normalization for the approximate reasoning. We present the conc...
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We study the problem of efficient, scalable set-sharing analysis of logic programs. We use the idea of representing sharing information as a pair of abstract substitutions, one of which is a worst-case sharing represe...
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We study the problem of efficient, scalable set-sharing analysis of logic programs. We use the idea of representing sharing information as a pair of abstract substitutions, one of which is a worst-case sharing representation called a clique set, which was previously proposed for the case of inferring pair-sharing. We use the clique-set representation for (1) inferring actual set-sharing information, and (2) analysis within a topdown framework. In particular, we define the abstract functions required by standard top-down analyses, both for sharing alone and also for the case of including freeness in addition to sharing. Our experimental evaluation supports the conclusion that, for inferring set-sharing, as it was the case for inferring pair-sharing, precision losses are limited, while useful efficiency gains are obtained. At the limit, the clique-set representation allowed analyzing some programs that exceeded memory capacity using classical sharing representations.
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