this paper demonstrates the applicability of automated reasoning to text processing, specifically to Question Answering. It is shown that the approach is feasible, effective, and scalable. A logic Prover has been impl...
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this paper demonstrates the applicability of automated reasoning to text processing, specifically to Question Answering. It is shown that the approach is feasible, effective, and scalable. A logic Prover has been implemented and integrated into a state-of-the-art Question Answering System.
Binary morphological operations are a building block in many computer vision applications. Several iterative morphological operations are commonly performed for image analysis resulting in a significant computational ...
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Prioritized logic programs (PLPs) have a mechanism of representing priority knowledge in logic programs. the declarative semantics of a PLP is given as preferred answer sets which are used for representing nonmonotoni...
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ISBN:
(数字)9783540398134
ISBN:
(纸本)3540201017
Prioritized logic programs (PLPs) have a mechanism of representing priority knowledge in logic programs. the declarative semantics of a PLP is given as preferred answer sets which are used for representing nonmonotonic reasoning as well as preference abduction. From the computational viewpoint, however, its implementation issues have little been studied and no sound procedure is known for computing preferred answer sets of PLPs. In this paper, we present a sound and complete procedure to compute all preferred answer sets of a PLP in answer set programming. the procedure is based on a program transformation from a PLP to a logic program and is realized on top of any procedure for answer set programming. the proposed technique also extends PLPs to handle dynamic preference and we address its application to legal reasoning.
Belief has been formally modelled using doxastic logics in recent decades. the possible worlds model provides an intuitive semantics for these logics. But it also commits us to the problem of logical omniscience. A nu...
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Belief has been formally modelled using doxastic logics in recent decades. the possible worlds model provides an intuitive semantics for these logics. But it also commits us to the problem of logical omniscience. A number of logics have been introduced to circumvent the problem. Of particular interest is the logic of awareness. In this paper we present a new method to put awareness into doxastic logic so as to get a flexible way to model actual belief. the underlying logics are two-dimensional logics. Two two-dimensional doxastic logics are given. In the first logic, a quite limited concept of actual belief is presented. In the second logic, two-dimensional and classical semantics are combined into a hybrid system.
the proceedings contain 292 papers. the topics discussed include: learning value predictors for the speculative execution of information gathering plans;logic programs for consistently querying data integration system...
the proceedings contain 292 papers. the topics discussed include: learning value predictors for the speculative execution of information gathering plans;logic programs for consistently querying data integration systems;query rewriting and answering under constraints in data integration systems;integrating multiple Internet directories by instance-based learning;a semantic framework for multimedia document adaptation;an ontology-based architecture for cooperative information agents;web page cleaning for web mining through feature weighting;a learning-based jam session system that imitates a player's personality model;getting serious about the development of computational humor;a tractability result for reasoning with incomplete first-order knowledge bases;practical partition-based theorem proving for large knowledge bases;and quantifying information and contradiction in propositional logicthrough test actions.
Disjunctive logicprogramming (DLP) is a very expressive formalism: it allows to express every property of finite structures that is decidable in the complexity class E∧ (NPNH). Despite the high expressiveness of DLP...
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Disjunctive logicprogramming (DLP) is a very expressive formalism: it allows to express every property of finite structures that is decidable in the complexity class E∧ (NPNH). Despite the high expressiveness of DLP, there are some simple properties, often arising in real-world applications, which cannot be encoded in a simple and natural manner. Among these, properties requiring to apply some arithmetic operators (like sum, times, count) on a set of elements satisfying some conditions, cannot be naturally expressed in DLP. To overcome this deficiency, in this paper we extend DLP by aggregate functions. We formally define the semantics of the new language, named DLP-4. We show the usefulness of the new constructs on relevant knowledge-based problems. We analyze the computational complexity of DLP-4, showing that the addition of aggregates does not bring a higher cost in that respect. We provide an implementation of the DLP-4 language in DLV- the state-of-the-art DLP system - and report on experiments which confirm the usefulness of the proposed extension also for the efficiency of the computation.
this panel brings together coaches to discuss all aspects of the practice - how to become a coach, choosing a coach, and describing what is to be an (in) effective coach. A coach watches, provides feedback, and sugges...
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ISBN:
(纸本)1581137516
this panel brings together coaches to discuss all aspects of the practice - how to become a coach, choosing a coach, and describing what is to be an (in) effective coach. A coach watches, provides feedback, and suggests subtle direction. the coach may be more - for example - an architect or team lead. the panelists will describe their positions and offer feedback. Panelists were asked to offer responses to three questions: • How did YOU become a coach? • What's the toughest thing you've had to do as a coach? • What's your advice for teams looking for a coach?
We propose a purely logical framework for planning in partially observable environments. Knowledge states are expressed in a suitable fragment of the epistemic logic S5. We show how to lift the effects of actions (bot...
We propose a purely logical framework for planning in partially observable environments. Knowledge states are expressed in a suitable fragment of the epistemic logic S5. We show how to lift the effects of actions (both physical actions and sensing actions) from the state level to the epistemic level. We show how progression, regression and plan generation can be achieved in our framework.
Degrees of information and of contradiction are investigated within a uniform propositional framework, based on test actions. We consider that the degree of information of a propositional formula is based on the cost ...
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Degrees of information and of contradiction are investigated within a uniform propositional framework, based on test actions. We consider that the degree of information of a propositional formula is based on the cost of actions needed to identify the truth values of each atomic proposition, while the degree of contradiction of a formula is based on the cost of actions needed to make the formula classically consistent. Our definitions are to a large extent independent of the underlying propositional logic;this flexibility is of prime importance since there is no unique, fully accepted logic for reasoning under inconsistency.
Sequence alignment is an important problem in computational biology. We compare two different approaches to the problem of optimally aligning two or more character strings: bounded dynamic programming (BDP), and divid...
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Sequence alignment is an important problem in computational biology. We compare two different approaches to the problem of optimally aligning two or more character strings: bounded dynamic programming (BDP), and divide-and-conquer frontier search (DCFS). the approaches are compared in terms of time and space requirements in 2 through 5 dimensions with sequences of varying similarity and length. While BDP performs better in two and three dimensions, it consumes more time and memory than DCFS for higher-dimensional problems.
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