15,736 research outputs found

    A Spectrum of Applications of Automated Reasoning

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    The likelihood of an automated reasoning program being of substantial assistance for a wide spectrum of applications rests with the nature of the options and parameters it offers on which to base needed strategies and methodologies. This article focuses on such a spectrum, featuring W. McCune's program OTTER, discussing widely varied successes in answering open questions, and touching on some of the strategies and methodologies that played a key role. The applications include finding a first proof, discovering single axioms, locating improved axiom systems, and simplifying existing proofs. The last application is directly pertinent to the recently found (by R. Thiele) Hilbert's twenty-fourth problem--which is extremely amenable to attack with the appropriate automated reasoning program--a problem concerned with proof simplification. The methodologies include those for seeking shorter proofs and for finding proofs that avoid unwanted lemmas or classes of term, a specific option for seeking proofs with smaller equational or formula complexity, and a different option to address the variable richness of a proof. The type of proof one obtains with the use of OTTER is Hilbert-style axiomatic, including details that permit one sometimes to gain new insights. We include questions still open and challenges that merit consideration.Comment: 13 page

    On Improving Local Search for Unsatisfiability

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    Stochastic local search (SLS) has been an active field of research in the last few years, with new techniques and procedures being developed at an astonishing rate. SLS has been traditionally associated with satisfiability solving, that is, finding a solution for a given problem instance, as its intrinsic nature does not address unsatisfiable problems. Unsatisfiable instances were therefore commonly solved using backtrack search solvers. For this reason, in the late 90s Selman, Kautz and McAllester proposed a challenge to use local search instead to prove unsatisfiability. More recently, two SLS solvers - Ranger and Gunsat - have been developed, which are able to prove unsatisfiability albeit being SLS solvers. In this paper, we first compare Ranger with Gunsat and then propose to improve Ranger performance using some of Gunsat's techniques, namely unit propagation look-ahead and extended resolution

    What UK graduate employers think they want and what university business schools think they provide

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    This is tha authors' PDF version of an article published in International Journal of Management Concepts and PhilosophyĀ© 2009. The definitive version is available at www.inderscience.comThis paper evaluates the increasing focus on the development of students' competencies and skills for management, in university business schools. The debate suggests that deeper understandings, concerning the role of managers are being sacrificed at the hands of an instrumentalist/technicist agenda focusing on competencies and skills. The paper adds to the discussion by scrutinising and applying theory from the literatures of occupational practice, knowledge and learning. Data is presented from sixty four job advertisements stipulating the competencies and skills required of applicants and which illustrate the premium put upon personal practice knowledge. By taking a critical management perspective students can begin to understand the social context and power-based nature of management practice in the workplace. While universities may try to further fulfil the 'narrow', industry-led, competency focus, early indications suggest that universities may possess a good deal of freedom in designing pedagogies supportive of a critical agenda

    Progress in AI Planning Research and Applications

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    Planning has made significant progress since its inception in the 1970s, in terms both of the efficiency and sophistication of its algorithms and representations and its potential for application to real problems. In this paper we sketch the foundations of planning as a sub-field of Artificial Intelligence and the history of its development over the past three decades. Then some of the recent achievements within the field are discussed and provided some experimental data demonstrating the progress that has been made in the application of general planners to realistic and complex problems. The paper concludes by identifying some of the open issues that remain as important challenges for future research in planning

    Knowledge Representation with Ontologies: The Present and Future

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    Recently, we have seen an explosion of interest in ontologies as artifacts to represent human knowledge and as critical components in knowledge management, the semantic Web, business-to-business applications, and several other application areas. Various research communities commonly assume that ontologies are the appropriate modeling structure for representing knowledge. However, little discussion has occurred regarding the actual range of knowledge an ontology can successfully represent

    Integrating Conflict Driven Clause Learning to Local Search

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    This article introduces SatHyS (SAT HYbrid Solver), a novel hybrid approach for propositional satisfiability. It combines local search and conflict driven clause learning (CDCL) scheme. Each time the local search part reaches a local minimum, the CDCL is launched. For SAT problems it behaves like a tabu list, whereas for UNSAT ones, the CDCL part tries to focus on minimum unsatisfiable sub-formula (MUS). Experimental results show good performances on many classes of SAT instances from the last SAT competitions
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