We revisit an application developed originally using abductive Inductive logicprogramming (ILP) for modeling inhibition in metabolic networks. the example data was derived from studies of the effects of toxins on rat...
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ISBN:
(纸本)3540784683
We revisit an application developed originally using abductive Inductive logicprogramming (ILP) for modeling inhibition in metabolic networks. the example data was derived from studies of the effects of toxins on rats using Nuclear Magnetic Resonance (NMR) time-trace analysis of their biofluids together with background knowledge representing a subset of the Kyoto Encyclopedia of Genes and Genomes (KEGG). We now apply two Probabilistic ILP (PILP) approaches-abductive Stochastic logic Programs (SLPs) and programming In Statistical modeling (PRISM) to the application. Both approaches support abductive learning and probability predictions. Abductive SLPs are a PILP framework that provides possible worlds semantics to SLPs through abduction. Instead of learning logic models from non-probabilistic examples as done in ILP, the PILP approach applied in this paper is based on a general technique for introducing probability labels within a standard scientific experimental setting involving control and treated data. Our results demonstrate that the PILP approach provides a way of learning probabilistic logic models from probabilistic examples, and the PILP models learned from probabilistic examples lead to a significant decrease in error accompanied by improved insight from the learned results compared withthe PILP models learned from non-probabilistic examples.
We propose a method of classifying XML documents and extracting XML schema from XML by inductive inference based on constraint logicprogramming. the goal of this work is to type a large collection of XML approximatel...
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ISBN:
(纸本)9781605580852
We propose a method of classifying XML documents and extracting XML schema from XML by inductive inference based on constraint logicprogramming. the goal of this work is to type a large collection of XML approximately but efficiently. this can also process XML code written in a different schema or even code which is schema-less. Our approach is intended to achieve identification based on the syntax and semantics of the XML documents by information extraction using ontology, and to support retrieval and data management. Our approach has three steps. the first step is XML to predicates, the second step is to compare predicates and classifies structures which represent similar meanings in different structures, and the last step is predicates to rules by using ontology and to maintain XML Schema. We evaluate similarity of data type and data range by using an ontology dictionary, and XML Schema is made from results of second and last step.
Uncertain information is present in many real applications e.g., medical domain, weather forecast, etc. the most common approaches for leading withthis information are based on probability however some times;it is di...
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ISBN:
(纸本)9783540766308
Uncertain information is present in many real applications e.g., medical domain, weather forecast, etc. the most common approaches for leading withthis information are based on probability however some times;it is difficult to find suitable probabilities about some events. In this paper, we present a possibilistic logicprogramming approach which is based on possibilistic logic and PStable semantics. Possibilistic logic is a logic of uncertainty tailored for reasoning under incomplete evidence and Pstable Semantics is a solid semantics which emerges from the fusion of non-monotonicreasoning and logicprogramming;moreover it is able to express answer set semantics, and has strong connections with paraconsistent logics.
Current Answer Set programming systems are built on nonmonotoniclogic programs without function symbols;as well-known, they lead to high undecidability in general. However, function symbols are highly desirable for v...
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ISBN:
(纸本)9783540755586
Current Answer Set programming systems are built on nonmonotoniclogic programs without function symbols;as well-known, they lead to high undecidability in general. However, function symbols are highly desirable for various applications, which challenges to find meaningful and decidable fragments of this setting. We present the class FDNC of logic programs which allows for function symbols, disjunction, nonmonotonic negation under answer set semantics, and constraints, while still retaining the decidability of the standard reasoning tasks. thanks to these features, they are a powerful formalism for rule-based modeling of applications with potentially infinite processes and objects, which allows also for common-sense reasoning. We show that consistency checking and brave reasoning are EXPTIME-complete in general, but have lower complexity for restricted fragments, and outline worst-case optimal reasoning procedures for these tasks. Furthermore, we present a finite representation of the possibly infinitely many infinite stable models of an FDNC program, which may be exploited for knowledge compilation purposes.
Two sets of rules are said to be strongly equivalent to each other if replacing one by the other within any logic program preserves the program's stable models. the familiar characterization of strong equivalence ...
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ISBN:
(纸本)9783540721994
Two sets of rules are said to be strongly equivalent to each other if replacing one by the other within any logic program preserves the program's stable models. the familiar characterization of strong equivalence of grounded programs in terms of the propositional logic of here-and-there is extended in this paper to a large class of logic programs with variables. this class includes, in particular, programs with conditional literals and cardinality constraints. the first-order version of the logic of here-and-there required for this purpose involves two additional non-intuitionistic axiom schemas.
Update of knowledge bases is becoming an important topic in Artificial Intelligence and a key problem in knowledge representation and reasoning. One of the latest ideas to update logic programs is choosing between mod...
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ISBN:
(纸本)9783540766308
Update of knowledge bases is becoming an important topic in Artificial Intelligence and a key problem in knowledge representation and reasoning. One of the latest ideas to update logic programs is choosing between models of Minimal Generalised Answer Sets to overcome disadvantages of previous approaches. this paper describes an implementation of the declarative version of updates sequences that has been proposed as an alternative to syntax-based semantics. One of the main contributions of this implementation is to use DLV's Weak Constraints to compute the model(s) of an update sequence, besides presenting the precise definitions proposed by the authors and an online solver. As a result;the paper makes an outline of the basic structure of the system, describes the employed technology, discusses the major process of computing the models;and illustrates the system through examples.
A forward reasoning engine is an indispensable component in many advanced knowledge-based systems with purposes of creation, discovery, or prediction. this paper presents a forward reasoning engine with general-purpos...
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ISBN:
(纸本)9783540748267
A forward reasoning engine is an indispensable component in many advanced knowledge-based systems with purposes of creation, discovery, or prediction. this paper presents a forward reasoning engine with general-purpose, named "FreeEnCal", which can interpret and perform inference rules defined and given by its users, draw fragments of various classical and/or non-classical logic systems formalized as different formal systems, draw empirical theorems of various formal theories constructed based on various logic systems, and perform deductive, inductive, and abductive reasoning automatically. FreeEnCal can be used as a ready-made forward reasoning engine serving as a core and fundamental component in various advanced knowledge-based systems as well as an alone forward reasoning engine with general-purpose. the paper presents our basic ideas to design and implement FreeEnCal, facilities provided by FreeEnCal, and some applications of FreeEnCal.
In logic programs, negation-as-failure has been used both for representing negative information and for providing default non-monotonic inference. In this paper we argue that this twofold role is not only unnecessary ...
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ISBN:
(纸本)3540482814
In logic programs, negation-as-failure has been used both for representing negative information and for providing default non-monotonic inference. In this paper we argue that this twofold role is not only unnecessary for the expressiveness of the language, but it also plays against declarative programming, especially if further negation symbols such as strong negation are also available. We therefore propose a new logicprogramming approach in which negation and default inference are independent, orthogonal concepts. Semantical characterization of this approach is given in the style of answer sets, but other approaches are also possible. Finally, we compare them withthe semantics for logic programs with two kinds of negation.
this paper presents systems for first-order intuitionistic logic and several of its extensions in which all the propositional rules are local, in the sense that, in applying the rules of the system, one needs only a f...
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ISBN:
(纸本)3540482814
this paper presents systems for first-order intuitionistic logic and several of its extensions in which all the propositional rules are local, in the sense that, in applying the rules of the system, one needs only a fixed amount of information about the logical expressions involved. the main source of non-locality is the contraction rules. We show that the contraction rules can be restricted to the atomic ones, provided we employ deep-inference, i.e., to allow rules to apply anywhere inside logical expressions. We further show that the use of deep inference allows for modular extensions of intuitionistic logic to Dummett's intermediate logic LC, Godel logic and classical logic. We present the systems in the calculus of structures, a proof theoretic formalism which supports deep-inference. Cut elimination for these systems are proved indirectly by simulating the cut-free sequent systems, or the hypersequent systems in the cases of Dummett's LC and Godel logic, in the cut free systems in the calculus of structures.
the proceedings contain 30 papers. the topics discussed include: formal verification of infinite state systems using Boolean methods;solving partial order constraints for LPO termination;computationally equivalent eli...
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ISBN:
(纸本)3540368345
the proceedings contain 30 papers. the topics discussed include: formal verification of infinite state systems using Boolean methods;solving partial order constraints for LPO termination;computationally equivalent elimination of conditions;on the correctness of bubbling;prepositional tree automata;hierarchical combination of intruder theories;feasible trace reconstruction for rewriting approximations;a terminating and confluent linear lambda calculus;structural proof theory as rewriting;checking conservability of overloaded definitions in higher-order logic;certified higher-order recursive path ordering;dealing withnon-orientable equations in rewriting induction;the CL-Atse protocol analyser;predictive labeling;termination of string rewriting with matrix interpretations;decidability of termination for semi-constructor TRSs, left-linear shallow TRSs and related systems;and higher-order orderings for normal rewriting.
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