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Although Inductive Logic Programming (ILP) is generally thought of as a research area at the intersection of machine learning and computational logic, Bergadano and Gunetti propose that most of the research in ILP has in fact come from machine learning, particularly in the evolution of inductive reasoning from pattern recognition, through initial approaches to symbolic machine learning, to recent techniques for learning relational concepts. In this book they provide an extended, up-to-date survey of ILP, emphasizing methods and systems suitable for software engineering applications, including inductive program development, testing, and maintenance. Inductive Logic Programming includes a definition of the basic ILP problem and its variations (incremental, with queries, for multiple predicates and predicate invention capabilities), a description of bottom-up operators and techniques (such as least general generalization, inverse resolution, and inverse implication), an analysis of top-down methods (mainly MIS and FOIL-like systems), and a survey of methods and languages for specifying inductive bias. Logic Programming series
This book constitutes the refereed proceedings of the 11th European Conference on Principles and Practice of Knowledge Discovery in Databases, PKDD 2007, held in Warsaw, Poland, co-located with ECML 2007, the 18th European Conference on Machine Learning. The 28 revised full papers and 35 revised short papers present original results on leading-edge subjects of knowledge discovery from conventional and complex data and address all current issues in the area.
Includes tutorials, lectures, and refereed papers on all aspects of logic programming, The Joint International Conference and Symposium on Logic Programming, sponsored by the Association for Logic Programming, includes tutorials, lectures, and refereed papers on all aspects of logic programming, including theoretical foundations, constraints, concurrency and parallelism, deductive databases, language design and implementation, nonmonotonic reasoning, and logic programming and the Internet.
Includes tutorials, lectures, and refereed papers on all aspects of logic programming, including theoretical foundations, constraints, concurrency and parallelism, deductive databases, language design and implementation, nonmonotonic reasoning, and logic programming and the Internet. The International Conference on Logic Programming, sponsored by the Association for Logic Programming, includes tutorials, lectures, and refereed papers on all aspects of logic programming, including theoretical foundations, constraints, concurrency and parallelism, deductive databases, language design and implementation, nonmonotonic reasoning, and logic programming and the Internet.
Includes tutorials, invited lectures, and refereed papers on all aspects of logic programming including: Constraints, Concurrency and Parallelism, Deductive Databases, Implementations, Meta and Higher-order Programming, Theory, and Semantic Analysis. September 2-6, 1996, Bonn, Germany Every four years, the two major international scientific conferences on logic programming merge in one joint event. JICSLP'96 is the thirteenth in the two series of annual conferences sponsored by The Association for Logic Programming. It includes tutorials, invited lectures, and refereed papers on all aspects of logic programming including: Constraints, Concurrency and Parallelism, Deductive Databases, Implementations, Meta and Higher-order Programming, Theory, and Semantic Analysis. The contributors are international, with strong contingents from the United States, United Kingdom, France, and Japan. Logic Programming series, Research Reports and Notes
The major theme of this book is Intelligent Agents. An agent is a hardware or software system that is autonomous, interactive with and reactive to its environment and other agents. An agent can also be pro-active in taking the initiative in goal-directed behaviour. Intelligent Agents are one of the most important and exciting areas of research and development in computer science today.
"This book provides analysis, characterization and refinement of software engineering data in terms of machine learning methods. It depicts applications of several machine learning approaches in software systems development and deployment, and the use of machine learning methods to establish predictive models for software quality while offering readers suggestions by proposing future work in this emerging research field"--Provided by publisher.
This book constitutes the refereed proceedings of the Third International Symposium on Intelligent Data Analysis, IDA-99 held in Amsterdam, The Netherlands in August 1999. The 21 revised full papers and 23 posters presented in the book were carefully reviewed and selected from a total of more than 100 submissions. The papers address all current aspects of intelligent data analysis; they are organized in sections on learning, visualization, classification and clustering, integration, applications and media mining.
This volume collects the papers selected for presentation at the IX Congress of the Italian Association for Arti?cial Intelligence (AI*IA), held in Milan at the University of Milano–Bicocca (September 21–23, 2005). On the one hand this congress continues the tradition of AI*IA in organizing its biannual s- enti?c meeting from 1989; on the other hand, this edition is a landmark in the involvement of the international community of arti?cial intelligence (AI), directly involving a broad number of experts from several countries in the P- gramCommittee. Moreover,the peculiar nature of scienti?c researchin arti?cial intelligence (which is intrinsically international) and several consolidated i...
This book constitutes the refereed proceedings of the 18th European Conference on Machine Learning, ECML 2007, held in Warsaw, Poland, September 2007, jointly with PKDD 2007. The 41 revised full papers and 37 revised short papers presented together with abstracts of four invited talks were carefully reviewed and selected from 592 abstracts submitted to both, ECML and PKDD. The papers present a wealth of new results in the area and address all current issues in machine learning.