Bibliografías temáticas / Rule based programming

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Literatura académica sobre el tema "Rule based programming"

Autor: Grafiati

Publicado: 4 de junio de 2021

Última modificación: 25 de mayo de 2024

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Artículos de revistas sobre el tema "Rule based programming"

APT, KRZYSZTOF R., and ERIC MONFROY. "Constraint programming viewed as rule-based programming." Theory and Practice of Logic Programming 1, no. 6 (November 2001): 713–50. http://dx.doi.org/10.1017/s1471068401000072.

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We study here a natural situation when constraint programming can be entirely reduced to rule-based programming. To this end we explain first how one can compute on constraint satisfaction problems using rules represented by simple first-order formulas. Then we consider constraint satisfaction problems that are based on predefined, explicitly given constraints. To solve them we first derive rules from these explicitly given constraints and limit the computation process to a repeated application of these rules, combined with labeling. We consider two types of rule here. The first type, that we call equality rules, leads to a new notion of local consistency, called rule consistency that turns out to be weaker than arc consistency for constraints of arbitrary arity (called hyper-arc consistency in Marriott & Stuckey (1998)). For Boolean constraints rule consistency coincides with the closure under the well-known propagation rules for Boolean constraints. The second type of rules, that we call membership rules, yields a rule-based characterization of arc consistency. To show feasibility of this rule-based approach to constraint programming, we show how both types of rules can be automatically generated, as CHR rules of Frühwirth (1995). This yields an implementation of this approach to programming by means of constraint logic programming. We illustrate the usefulness of this approach to constraint programming by discussing various examples, including Boolean constraints, two typical examples of many valued logics, constraints dealing with Waltz's language for describing polyhedral scenes, and Allen's qualitative approach to temporal logic.

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Kirchner, Claude, and Christophe Ringeissen. "Rule-Based Constraint Programming." Fundamenta Informaticae 34, no. 3 (1998): 225–62. http://dx.doi.org/10.3233/fi-1998-34302.

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BROWNE, JAMES C., ALLEN EMERSON, MOHAMED G. GOUDA, DANIEL P. MIRANKER, ALOYSIUS MOK, LANCE OBERMEYER, FURMAN HADDIX, RWO-HSI WANG, and SARAH CHODROW. "MODULARITY AND RULE-BASED PROGRAMMING." International Journal on Artificial Intelligence Tools 04, no. 01n02 (June 1995): 201–18. http://dx.doi.org/10.1142/s0218213095000115.

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In this paper we describe a purely declarative method for introducing modularity into forward-chaining, rule-based languages. The method is enforced by the syntax of the language and includes the ability to parameterize the rule groups. We also describe the Venus programming environment, which implements the presented ideas. Drawing from two of three Venus applications developed to date, we illustrate how this form of modularity contributes directly to the resolution of certain software engineering problems associated with rule languages. We also discuss key implementation details and present performance data.

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Drewes, Frank, Berthold Hoffmann, Raimund Klein, and Mark Minas. "Rule-Based Programming with Diaplan." Electronic Notes in Theoretical Computer Science 127, no. 1 (March 2005): 15–26. http://dx.doi.org/10.1016/j.entcs.2004.12.027.

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Paschke, Adrian. "A Report on the Ninth International Web Rule Symposium." AI Magazine 37, no. 1 (April 13, 2016): 105–6. http://dx.doi.org/10.1609/aimag.v37i1.2634.

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The annual International Web Rule Symposium (RuleML) is an international conference on research, applications, languages and standards for rule technologies. RuleML is a leading conference to build bridges between academe and industry in the field of rules and its applications, especially as part of the semantic technology stack. It is devoted to rule-based programming and rule-based systems including production rules systems, logic programming rule engines, and business rule engines/business rule management systems; semantic web rule languages and rule standards; rule-based event processing languages (EPLs) and technologies; and research on inference rules, transformation rules, decision rules, production rules, and ECA rules. The 9th International Web Rule Symposium (RuleML 2015) was held in Berlin, Germany, August 2-5. This report summarizes the events of that conference.

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Sanford, David L., and J. W. Roach. "Using rule‐based computer programming to unify communication rules research." Research on Language & Social Interaction 21, no. 1-4 (January 1987): 63–92. http://dx.doi.org/10.1080/08351818709389285.

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Xu, Yuzhao, Yanjing Sun, Zhanguo Ma, Hongjie Zhao, Yanfen Wang, and Nannan Lu. "Attribute Selection Based Genetic Network Programming for Intrusion Detection System." Journal of Advanced Computational Intelligence and Intelligent Informatics 26, no. 5 (September 20, 2022): 671–83. http://dx.doi.org/10.20965/jaciii.2022.p0671.

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Intrusion detection, as a technology used to monitor abnormal behavior and maintain network security, has attracted many researchers’ attention in recent years. Thereinto, association rule mining is one of the mainstream methods to construct intrusion detection systems (IDS). However, the existing association rule algorithms face the challenges of high false positive rate and low detection rate. Meanwhile, too many rules might lead to the uncertainty increase that affects the performance of IDS. In order to tackle the above problems, a modified genetic network programming (GNP) is proposed for class association rule mining. Specifically, based on the property that node connections in the directed graph structure of GNP can be used to construct attribute associations, we propose to introduce information gain into GNP node selection. The most important attributes are thus selected, and the irrelevant attributes are removed before the rule is extracted. Moreover, not only the uncertainty among the class association rules is alleviated and also time consumption is reduced. The extracted rules can be applied to any classifier without affecting the detection performance. Experiment results based on NSL-KDD and KDDCup99 verify the performance of our proposed algorithm.

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BIKAKIS, ANTONIS, PAUL FODOR, ADRIAN GIURCA, and LEORA MORGENSTERN. "Introduction to the special issue on the International Web Rule Symposia 2012–2014." Theory and Practice of Logic Programming 16, no. 3 (March 7, 2016): 243–46. http://dx.doi.org/10.1017/s1471068416000028.

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The annual International Web Rule Symposium (RuleML) is an international conference on research, applications, languages, and standards for rule technologies. It has evolved from an annual series of international workshops since 2002, international conferences in 2005 and 2006, and international symposia since 2007. It is the flagship event of the Rule Markup and Modeling Initiative (RuleML, http://ruleml.org), a nonprofit umbrella organization of several technical groups from academia, industry, and government working on rule technology and its applications. RuleML is the leading conference to build bridges between academia and industry in the field of rules and its applications, especially as part of the semantic technology stack. It is devoted to rule-based programming and rule-based systems including production rules systems, logic programming rule engines, and business rules engines/business rules management systems; Semantic Web rule languages and rule standards (e.g., RuleML, SWRL, RIF, PRR, SBVR, DMN, CL, Prolog); rule-based event processing languages and technologies; and research on inference rules, transformation rules, decision rules, production rules, and ECA rules.

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Lamma, E., L. Maestrami, P. Mello, F. Riguzzi, and S. Storari. "Rule-based Programming for Building Expert Systems." Electronic Notes in Theoretical Computer Science 59, no. 4 (November 2001): 397–411. http://dx.doi.org/10.1016/s1571-0661(04)00299-3.

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Olmedo-Aguirre, José Oscar, and Marisol Vázquez-Tzompantzi. "Flexible Rule-Based Programming for Autonomic Computing." Research in Computing Science 105, no. 1 (December 31, 2015): 63–73. http://dx.doi.org/10.13053/rcs-105-1-6.

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Tesis sobre el tema "Rule based programming"

Kuo, Yung-Li. "Developing a rule-based expert system with C programming language." Virtual Press, 1988. http://liblink.bsu.edu/uhtbin/catkey/552943.

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Expert system techniques are now being incorporated successfully in commercial computer software packages. This thesis introduces the techniques of developing a rule-based expert system in a general-purpose programming language -- C. The topics of this thesis include significance of expert system shells and approaches used, structure of the knowledge base, loading of the knowledge base, manipulation of the probabilities of rule attributes, and implementation of the inference engine. The inference engine uses the information that users supply to find an object that matches. Today C language is one of the most popular programming languages in use and C compilers consistently produce extremely fast and efficient executable programs. Thisthesisdemonstrates that C language is an appropriate computer language for a rule-based expert system. Department of Computer Science

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Soltan-Zadeh, Yasaman. "Improved rule-based document representation and classification using genetic programming." Thesis, Royal Holloway, University of London, 2011. http://repository.royalholloway.ac.uk/items/479a1773-779b-8b24-b334-7ed485311abe/8/.

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Williamson, C. J. "Computer aided process control systems synthesis using rule-based programming." Thesis, University of Canterbury. Chemical Engineering, 1989. http://hdl.handle.net/10092/9407.

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Current steady-state process simulators have greatly increased the speed and efficiency of the development of Process Flow Diagrams. Chemical Engineers would benefit in the same way from a Computer Aided Design package to assist with generating completed Piping and Instrument Diagrams. Despite the many theoretical methods available in the control science area there is no single and complete available solution to the problem of synthesising control systems for whole chemical processes and therefore no concrete basis from which to develop a computer program. Design activities rely on a significant experience factor and this element has largely been ignored especially in control systems synthesis. The recent emergence of rule-based programming allows this "experience" dimension to be added to software. Although there is previous work in the literature on expert systems for distillation column control systems synthesis there is very little published on programs for other unit operations or the whole plant problem. In this project the problem of how to set up an expert system for whole plant control systems synthesis was addressed. As a preliminary step this required that expert systems for control systems synthesis for unit operations be written. The necessary knowledge to do this for distillation columns, heat exchangers and reactors was sourced from the literature and programs developed for each using a shell written in a version of Prolog. These programs were coordinated to work together and provide controllable solutions to whole process control problems using a matrix representation of the relationship between control objectives and manipulated variables developed in structural controllability analysis. This provided the framework for a prototype whole plant program. The operation of all the programs is illustrated using typical examples and their rule bases included in appendices to the thesis. The work demonstrated that, with more extensive rulebases than it was possible to develop in the time available for this project including access to theoretical methods when required, expert systems could provide a useful solution to both unit operation and whole plant control systems synthesis problems.

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Pappa, Gisele Lobo. "Automatically evolving rule induction algorithms with grammar-based genetic programming." Thesis, University of Kent, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.445792.

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In the last 30 years, research in the field of rule induction algorithms produced a large number of algorithms. However, these algorithms are usually obtained from the combination of a basic rule induction algorithm (typically following the sequential covering approach) with new evaluation functions, pruning methods and stopping criteria for refining or producing rules, generating many "new" and more sophisticated sequential covering algorithms. We cannot deny that these attempts to improve the basic sequential covering ~approach have succeeded. Hence, if manually changing these major components of rule induction algorithms can result in new, significantly better ones, why not to automate this process to make it more cost-effective? This is the core idea of this work: to automate the process of designing rule induction algorithms by means of grammar-based genetic programming. Grammar-based Genetic Programming (GGP) is a special type of evolutionary algorithm used to automatically evolve computer programs. The most interesting feature of this type of algorithm is that it incorporates a grammar into its search mechanism, which expresses prior knowledge about the problem being solved. Since we have a lot of previous knowledge about how humans design rule induction algorithms, this type of algorithm is intuitively a suitable tool to automatically evolve rule induction algorithms. The grammar given to the proposed GGP system includes knowledge about how humans- design rule induction algorithms, and also presents some new elements which could work in rule induction algorithms, but to the best of our knowledge were not previously tested. The GG P system aims to evolve rule induction algorithms under two different frameworks, as follows. In the first framework, the GGP is used to evolve robust rule induction algorithms, i.e., algorithms which were designed to be applied to virtually any classification data set, like a manually-designed rule induction algorithm. In the second framework, the GGP is applied to evolve rule induction algorithms tailored to a specific application XVI domain, i.e., rule induction algorithms tailored to a single data set. Note that the latter framework is hardly feasible on a hard scale in the case of conventional, manually-designed algorithms, since the number of classification data sets greatly outnumbers the number of rule induction algorithms designers. However, it is clearly feasible on a large scale when using the proposed system, which automates the process of rule induction algorithm design and implementation. Overall, extensive computational experiments with 20 VCI data sets and 5 bioinformatics data sets showed that effective rule induction algorithms can be automatically generated using the GGP in both frameworks. Moreover, the automatically evolved rule induction algorithms were shown to be competitive with (and overall slightly better than) four well-known manually designed rule induction algorithms when comparing their predictive accuracies. The proposed GGP system was also compared to a grammar-based hillclimbing system, and experimental results showed that the GGP system is a more effective method to evolve rule induction algorithms than the grammar-based hillclimbing method. At last, a multi-objective version of the GGP (based on the concept of Pareto dominance) was also proposed, and experiments were performed to evolve robust rule induction algorithms which generate both accurate and simple models. The results showed that in most of the cases the GGP system can produce rule induction algorithms which are competitive in predictive accuracy to wellknown human-designed rule induction algorithms, but generate simpler classification modes - i.e., smaller rule sets, intuitively easier to be interpreted by the user.

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Liu, Youzhong. "Rule warehouse system for knowledge sharing and business collaboration." [Gainesville, Fla.] : University of Florida, 2001. http://etd.fcla.edu/etd/uf/2001/anp4027/Youzhong%5FLiu%5FDissertation.pdf.

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Thesis (Ph. D.)--University of Florida, 2001. Title from first page of PDF file. Document formatted into pages; contains xi, 121 p.; also contains graphics. Vita. Includes bibliographical references (p. 113-120).

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Lum, Bik. "A rule-based analysis system for Chinese sentences /." [Hong Kong : University of Hong Kong], 1989. http://sunzi.lib.hku.hk/hkuto/record.jsp?B1240231X.

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Lakkaraju, Sai Kiran, University of Western Sydney, of Science Technology and Environment College, and School of Computing and Information Technology. "A SLDNF based formalization for updates and abduction." THESIS_CSTE_CIT_Lakkaraju_S.xml, 2001. http://handle.uws.edu.au:8081/1959.7/381.

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Knowledge representation and inference are the backbone of artificial intelligence, and logic programming is one of the most widely used knowledge representation tools. Logic programming with deduction/induction/abduction as the reasoning technique is serving numerous fields of artificial intelligence. In dynamic domains where there are constant changes in knowledge, updating the knowledge base is crucial to keep it stable. This thesis investigates the issues in updating the knowledge base. Two types of logic program based updates are considered, simple fact based updates where the knowledge base is updated by a simple fact, and rule based updates where the knowledge base is updated by a rule. A SLDNF based procedural approach is proposed to implement such updates. This thesis also investigates the issues involved in simple fact based and rule based abduction, and it is observed that updates are closely related to abduction. A SLDNF based procedural approach to perform simple fact/rule based updates and abduction is proposed as a result of this study Master of Science (Hons)

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Sahin, Yavuz. "A Programming Framework To Implement Rule-based Target Detection In Images." Master's thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/12610213/index.pdf.

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An expert system is useful when conventional programming techniques fall short of capturing human expert knowledge and making decisions using this information. In this study, we describe a framework for capturing expert knowledge under a decision tree form and this framework can be used for making decisions based on captured knowledge. The framework proposed in this study is generic and can be used to create domain specific expert systems for different problems. Features are created or processed by the nodes of decision tree and a final conclusion is reached for each feature. Framework supplies 3 types of nodes to construct a decision tree. First type is the decision node, which guides the search path with its answers. Second type is the operator node, which creates new features using the inputs. Last type of node is the end node, which corresponds to a conclusion about a feature. Once the nodes of the tree are developed, then user can interactively create the decision tree and run the supplied inference engine to collect the result on a specific problem. The framework proposed is experimented with two case studies &quot Airport Runway Detection in High Resolution Satellite Images&quot and &quot Urban Area Detection in High Resolution Satellite Images&quot . In these studies linear features are used for structural decisions and Scale Invariant Feature Transform (SIFT) features are used for testing existence of man made structures.

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Terfloth, Kirsten [Verfasser]. "A rule-based programming model for wireless sensor networks / Kirsten Terfloth." Berlin : Freie Universität Berlin, 2009. http://d-nb.info/1023664135/34.

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Mehldau, Gerhard 1959. "A RULE-BASED PROGRAMMING LANGUAGE AND ITS APPLICATION TO IMAGE RECOGNITION." Thesis, The University of Arizona, 1986. http://hdl.handle.net/10150/276360.

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Libros sobre el tema "Rule based programming"

Kowalski, Thaddeus J., and Leon S. Levy, eds. Rule-Based Programming. Boston, MA: Springer US, 1996. http://dx.doi.org/10.1007/978-1-4613-1435-6.

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Kowalski, Thaddeus J. Rule-Based Programming. Boston, MA: Springer US, 1996.

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Kowalski, Thaddeus J. Rule-based programming. Boston: Kluwer Academic Publishers, 1996.

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Bassiliades, Nick, Guido Governatori, and Adrian Paschke, eds. Rule-Based Reasoning, Programming, and Applications. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22546-8.

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United States. National Aeronautics and Space Administration. Scientific and Technical Information Branch., ed. A rule based computer aided design system. [Washington, DC: National Aeronautics and Space Administration, Scientific and Technical Information Branch, 1986.

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Lee, Brownston, ed. Programming expert systems in OPS5: An introduction to rule-based programming. Reading, Mass: Addison-Wesley, 1985.

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Dutta, Soumitra. Integrating case based and rule based reasoning: The possibilistic connection. Fontainebleau, France: INSEAD, 1990.

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ACM Special Interest Group on Programming Languages., ed. Proceedings of the 2002 ACM SIGPLAN Workshop on Rule-Based Programming : RULE '02 : Pittsburgh, Pennsylvania, USA, October 5, 2002. New York, N.Y: Association for Computing Machinery, c2002., 2002.

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Expert systems programming: Practical techniques for rule-based systems. New York: Wiley, 1989.

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Logical foundations for rule-based systems. Berlin: Springer, 2006.

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Capítulos de libros sobre el tema "Rule based programming"

Mohan, Chilukuri Krishna. "Rule Based Programming." In Frontiers of Expert Systems, 99–131. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4509-5_4.

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Nalepa, Grzegorz J., Szymon Bobek, Antoni Ligęza, and Krzysztof Kaczor. "HalVA - Rule Analysis Framework for XTT2 Rules." In Rule-Based Reasoning, Programming, and Applications, 337–44. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22546-8_27.

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Nalepa, Grzegorz J., Szymon Bobek, Antoni Ligęza, and Krzysztof Kaczor. "Algorithms for Rule Inference in Modularized Rule Bases." In Rule-Based Reasoning, Programming, and Applications, 305–12. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22546-8_24.

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Rotolo, Antonino, and Leendert van der Torre. "Rules, Agents and Norms: Guidelines for Rule-Based Normative Multi-Agent Systems." In Rule-Based Reasoning, Programming, and Applications, 52–66. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22546-8_6.

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McGuire, B. R., and W. G. Wee. "Rule-Based Programming for Industrial Automation." In Artificial Intelligence in Design, 415–35. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-74354-2_17.

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Bǎdicǎ, Costin, Lars Braubach, and Adrian Paschke. "Rule-Based Distributed and Agent Systems." In Rule-Based Reasoning, Programming, and Applications, 3–28. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22546-8_3.

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Damásio, Carlos Viegas, Anastasia Analyti, and Grigoris Antoniou. "Modularity in the Rule Interchange Format." In Rule-Based Reasoning, Programming, and Applications, 313–28. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22546-8_25.

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Antoniou, Grigoris. "Rule-Based Activity Recognition in Ambient Intelligence." In Rule-Based Reasoning, Programming, and Applications, 1. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22546-8_1.

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Stojanovic, Nenad, and Alexander Artikis. "On Complex Event Processing for Real-Time Situational Awareness." In Rule-Based Reasoning, Programming, and Applications, 114–21. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22546-8_10.

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Anicic, Darko, Sebastian Rudolph, Paul Fodor, and Nenad Stojanovic. "Retractable Complex Event Processing and Stream Reasoning." In Rule-Based Reasoning, Programming, and Applications, 122–37. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22546-8_11.

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Actas de conferencias sobre el tema "Rule based programming"

Weise, Thomas, Michael Zapf, and Kurt Geihs. "Rule-based Genetic Programming." In 2007 2nd Bio-Inspired Models of Network, Information and Computing Systems (BIONETICS). IEEE, 2007. http://dx.doi.org/10.1109/bimnics.2007.4610073.

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Weise, Thomas, Michael Zapf, and Kurt Geihs. "Rule-based Genetic Programming." In 2nd International ICST Conference on Bio-Inspired Models of Network, Information, and Computing Systems. IEEE, 2007. http://dx.doi.org/10.4108/icst.bionetics2007.2395.

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Yu, Wenshan, and Rakesh M. Verma. "Visualization of rule-based programming." In the 2008 ACM symposium. New York, New York, USA: ACM Press, 2008. http://dx.doi.org/10.1145/1363686.1363976.

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Li, Xianneng, and Kotaro Hirasawa. "Extended rule-based genetic network programming." In Proceeding of the fifteenth annual conference companion. New York, New York, USA: ACM Press, 2013. http://dx.doi.org/10.1145/2464576.2464655.

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Roman, Gruia-Catalin, Rose F. Gamble, and William E. Ball. "Seeking concurrency in rule-based programming." In the 14th international conference. New York, New York, USA: ACM Press, 1992. http://dx.doi.org/10.1145/143062.143118.

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Roman, G. C., R. F. Gamble, and W. E. Ball. "Seeking concurrency in rule-based programming." In International Conference on Software Engineering. IEEE, 1992. http://dx.doi.org/10.1109/icse.1992.753502.

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Apt, Krzysztof R., and Sebastian Brand. "Schedulers for rule-based constraint programming." In the 2003 ACM symposium. New York, New York, USA: ACM Press, 2003. http://dx.doi.org/10.1145/952532.952537.

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Marin, M., and T. Ida. "Rule-based programming with /spl rho/Log." In Seventh International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC'05). IEEE, 2005. http://dx.doi.org/10.1109/synasc.2005.61.

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Menzies, Tim, and Lindsay Mason. "Some prolog macros for rule-based programming." In the 2002 ACM SIGPLAN workshop. New York, New York, USA: ACM Press, 2002. http://dx.doi.org/10.1145/570186.570194.

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Bianchi, Domenico, Luciano Rolando, Lorenzo Serrao, Simona Onori, Giorgio Rizzoni, Nazar Al-Khayat, Tung-Ming Hsieh, and Pengju Kang. "A Rule-Based Strategy for a Series/Parallel Hybrid Electric Vehicle: An Approach Based on Dynamic Programming." In ASME 2010 Dynamic Systems and Control Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/dscc2010-4233.

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Dynamic programming (DP) provides the optimal global solution to the energy management problem for hybrid electric vehicles (HEVs), but needs complete a-priori knowledge of the driving cycle and has high computational requirements. This article presents a possible methodology to extract rules from the dynamic programming solution to design an implementable rule-based strategy. The case study considered is a series/parallel HEV, in which a clutch allows to switch from one configuration to another. The strategy works according to a two layer policy: the supervisory controller, which decides the powertrain configuration (either series or parallel), and the energy management, which decides the power split. The process of deriving the rules from the optimal solution is described. Then, the performance of the resulting rule-based strategy is studied and compared with the solution given by the dynamic programming, which functions as a benchmark.

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Informes sobre el tema "Rule based programming"

Kelly, Luke. Lessons learnt from humanitarian negotiations with the Taliban, 1996-2001. Institute of Development Studies (IDS), September 2021. http://dx.doi.org/10.19088/k4d.2021.11.

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This rapid literature review finds that humanitarian actors responded in a variety of ways to Taliban actions limiting principled aid in the country during the period of their rule (1996-2001). The report is focused on the findings around humanitarian negotiation and the strategy of humanitarian actors in response to Taliban policies limiting women's ability to work for humanitarian organisations or access services. The findings are not intended to imply parallels with the current situation in Afghanistan. Evidence is in the form of a number of evaluations, academic articles and lessons learned papers on negotiating with the Taliban. It discusses the methods of negotiating with the Taliban (e.g. co-ordination, working with the leadership or rank-and-file), the content of negotiations and particularly the question of reaching agreement on women’s rights, as well as humanitarian actors’ negotiating capacity. There is less discussion on the negotiation of specific programmes (e.g. anti-gender-based violence programmes). Due to the different goals and principles of humanitarian actors, as well as different ideas of feasibility, conclusions on the effectiveness of negotiating tactics vary. Strategies therefore cannot be judged as 'successful' without reference to a conception of what is most important in humanitarian programming, and the constraints of the situation. The review highlights lessons on good negotiating practices. The main issue being negotiated was the clash between the Taliban's restrictions on women and humanitarian actors' aim of providing aid to all, including women, according to need. Various strategies were used to persuade the Taliban to consent to principled aid. This review considers aid agency negotiating strategy and tactics, as well as the underlying interests and constraints that may make negotiations more or less successful.

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Kelly, Luke. Lessons Learnt from Humanitarian Negotiations with the Taliban, 1996-2001. Institute of Development Studies (IDS), September 2021. http://dx.doi.org/10.19088/k4d.2021.126.

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Kelly, Luke. Lessons Learnt from Humanitarian Negotiations with the Taliban, 1996-2001. Institute of Development Studies, September 2021. http://dx.doi.org/10.19088/k4d.2021.119.

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Avis, William. Refugee and Mixed Migration Displacement from Afghanistan. Institute of Development Studies (IDS), August 2021. http://dx.doi.org/10.19088/k4d.2022.002.

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This rapid literature review summarises evidence and key lessons that exist regarding previous refugee and mixed migration displacement from Afghanistan to surrounding countries. The review identified a diverse literature that explored past refugee and mixed migration, with a range of quantitative and qualitative studies identified. A complex and fluid picture is presented with waves of mixed migration (both outflow and inflow) associated with key events including the: Soviet–Afghan War (1979–1989); Afghan Civil War (1992–96); Taliban Rule (1996–2001); War in Afghanistan (2001–2021). A contextual picture emerges of Afghans having a long history of using mobility as a survival strategy or as social, economic and political insurance for improving livelihoods or to escape conflict and natural disasters. Whilst violence has been a principal driver of population movements among Afghans, it is not the only cause. Migration has also been associated with natural disasters (primarily drought) which is considered a particular issue across much of the country – this is associated primarily with internal displacement. Further to this, COVID-19 is impacting upon and prompting migration to and from Afghanistan. Data on refugee and mixed migration movement is diverse and at times contradictory given the fluidity and the blurring of boundaries between types of movements. Various estimates exist for numbers of Afghanistan refugees globally. It is also important to note that migratory flows are often fluid involving settlement in neighbouring countries, return to Afghanistan. In many countries, Afghani migrants and refugees face uncertain political situations and have, in recent years, been ‘coerced’ into returning to Afghanistan with much discussion of a ‘return bias’ being evident in official policies. The literature identified in this report (a mix of academic, humanitarian agency and NGO) is predominantly focused on Pakistan and Iran with a less established evidence base on the scale of Afghan refugee and migrant communities in other countries in the region. . Whilst conflict has been a primary driver of displacement, it has intersected with drought conditions and poor adherence to COVID-19 mitigation protocols. Past efforts to address displacement internationally have affirmed return as the primary objective in relation to durable solutions; practically, efforts promoted improved programming interventions towards creating conditions for sustainable return and achieving improved reintegration prospects for those already returned to Afghanistan.

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