165,450 research outputs found
Computing Preferred Answer Sets by Meta-Interpretation in Answer Set Programming
Most recently, Answer Set Programming (ASP) is attracting interest as a new
paradigm for problem solving. An important aspect which needs to be supported
is the handling of preferences between rules, for which several approaches have
been presented. In this paper, we consider the problem of implementing
preference handling approaches by means of meta-interpreters in Answer Set
Programming. In particular, we consider the preferred answer set approaches by
Brewka and Eiter, by Delgrande, Schaub and Tompits, and by Wang, Zhou and Lin.
We present suitable meta-interpreters for these semantics using DLV, which is
an efficient engine for ASP. Moreover, we also present a meta-interpreter for
the weakly preferred answer set approach by Brewka and Eiter, which uses the
weak constraint feature of DLV as a tool for expressing and solving an
underlying optimization problem. We also consider advanced meta-interpreters,
which make use of graph-based characterizations and often allow for more
efficient computations. Our approach shows the suitability of ASP in general
and of DLV in particular for fast prototyping. This can be fruitfully exploited
for experimenting with new languages and knowledge-representation formalisms.Comment: 34 pages, appeared as a Technical Report at KBS of the Vienna
University of Technology, see http://www.kr.tuwien.ac.at/research/reports
Hipster: Integrating Theory Exploration in a Proof Assistant
This paper describes Hipster, a system integrating theory exploration with
the proof assistant Isabelle/HOL. Theory exploration is a technique for
automatically discovering new interesting lemmas in a given theory development.
Hipster can be used in two main modes. The first is exploratory mode, used for
automatically generating basic lemmas about a given set of datatypes and
functions in a new theory development. The second is proof mode, used in a
particular proof attempt, trying to discover the missing lemmas which would
allow the current goal to be proved. Hipster's proof mode complements and
boosts existing proof automation techniques that rely on automatically
selecting existing lemmas, by inventing new lemmas that need induction to be
proved. We show example uses of both modes
Adaptive logic characterizations of input/output logic
We translate unconstrained and constrained input/output logics as introduced by Makinson and van der Torre to modal logics, using adaptive logics for the constrained case. The resulting reformulation has some additional benefits. First, we obtain a proof-theoretic (dynamic) characterization of input/output logics. Second, we demonstrate that our framework naturally gives rise to useful variants and allows to express important notions that go beyond the expressive means of input/output logics, such as violations and sanctions
A dual process account of creative thinking
This article explicates the potential role played by type 1 thinking (automatic, fast) and type 2 thinking (effortful, logical) in creative thinking. The relevance of Evans's (2007) models of conflict of dual processes in thinking is discussed with regards to creative thinking. The role played by type 1 thinking and type 2 thinking during the different stages of creativity (problem finding and conceptualization, incubation, illumination, verification and dissemination) is discussed. It is proposed that although both types of thinking are active in creativity, the extent to which they are active and the nature of their contribution to creativity will vary between stages of the creative process. Directions for future research to test this proposal are outlined; differing methodologies and the investigation of different stages of creative thinking are discussed. © Taylor & Francis Group, LLC
Fault diagnosis and process monitoring through model-based case based reasoning
In this paper, we present a method for the fault detection and isolation based on the residual generation coupled with a case based reasoning approach. The main idea is to reconstruct the outputs of the system from the measurement using the extended Kalman filter. The estimations completed with qualitative information are included in a Case Based Reasoning system in order to discriminate the possible faults and to have a reliable diagnosis. The reference model is simulated by the dynamic hybrid simulator, PrODHyS. The use of this method is illustrated through an application in the field of chemical proces
A Goal-Directed Implementation of Query Answering for Hybrid MKNF Knowledge Bases
Ontologies and rules are usually loosely coupled in knowledge representation
formalisms. In fact, ontologies use open-world reasoning while the leading
semantics for rules use non-monotonic, closed-world reasoning. One exception is
the tightly-coupled framework of Minimal Knowledge and Negation as Failure
(MKNF), which allows statements about individuals to be jointly derived via
entailment from an ontology and inferences from rules. Nonetheless, the
practical usefulness of MKNF has not always been clear, although recent work
has formalized a general resolution-based method for querying MKNF when rules
are taken to have the well-founded semantics, and the ontology is modeled by a
general oracle. That work leaves open what algorithms should be used to relate
the entailments of the ontology and the inferences of rules. In this paper we
provide such algorithms, and describe the implementation of a query-driven
system, CDF-Rules, for hybrid knowledge bases combining both (non-monotonic)
rules under the well-founded semantics and a (monotonic) ontology, represented
by a CDF Type-1 (ALQ) theory. To appear in Theory and Practice of Logic
Programming (TPLP
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