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Book Proceedings of the ML 92 Workshop on Machine Discovery

Download or read book Proceedings of the ML 92 Workshop on Machine Discovery written by Jan M. Zytkow and published by . This book was released on 1992 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Machine Discovery

    Book Details:
  • Author : Jan Zytkow
  • Publisher : Springer Science & Business Media
  • Release : 2013-03-09
  • ISBN : 9401721246
  • Pages : 229 pages

Download or read book Machine Discovery written by Jan Zytkow and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt: Human and machine discovery are gradual problem-solving processes of searching large problem spaces for incompletely defined goal objects. Research on problem solving has usually focused on searching an `instance space' (empirical exploration) and a `hypothesis space' (generation of theories). In scientific discovery, searching must often extend to other spaces as well: spaces of possible problems, of new or improved scientific instruments, of new problem representations, of new concepts, and others. This book focuses especially on the processes for finding new problem representations and new concepts, which are relatively new domains for research on discovery. Scientific discovery has usually been studied as an activity of individual investigators, but these individuals are positioned in a larger social structure of science, being linked by the `blackboard' of open publication (as well as by direct collaboration). Even while an investigator is working alone, the process is strongly influenced by knowledge and skills stored in memory as a result of previous social interactions. In this sense, all research on discovery, including the investigations on individual processes discussed in this book, is social psychology, or even sociology.

Book Machine Learning Proceedings 1992

Download or read book Machine Learning Proceedings 1992 written by Peter Edwards and published by Morgan Kaufmann. This book was released on 2014-06-28 with total page 497 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning Proceedings 1992

Book Scientific and Technical Aerospace Reports

Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1992 with total page 1572 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Proceedings of the Sixteenth Annual Conference of the Cognitive Science Society

Download or read book Proceedings of the Sixteenth Annual Conference of the Cognitive Science Society written by Ashwin Ram and published by Routledge. This book was released on 2019-05-23 with total page 1014 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume features the complete text of all regular papers, posters, and summaries of symposia presented at the 16th annual meeting of the Cognitive Science Society.

Book Information  Statistics And Induction In Science   Proceedings Of The Conference  Isis  96

Download or read book Information Statistics And Induction In Science Proceedings Of The Conference Isis 96 written by David L Dowe and published by World Scientific. This book was released on 1996-07-29 with total page 423 pages. Available in PDF, EPUB and Kindle. Book excerpt: This conference will explore the use of computational modelling to understand and emulate inductive processes in science. The problems involved in building and using such computer models reflect methodological and foundational concerns common to a variety of academic disciplines, especially statistics, artificial intelligence (AI) and the philosophy of science. This conference aims to bring together researchers from these and related fields to present new computational technologies for supporting or analysing scientific inference and to engage in collegial debate over the merits and difficulties underlying the various approaches to automating inductive and statistical inference.The proceedings also include abstracts by the invited speakers (J R Quinlan, J J Rissanen, M Minsky, R J Solomonoff & H Kyburg, Jr.).

Book Discovery Science

    Book Details:
  • Author : Petra Kralj Novak
  • Publisher : Springer Nature
  • Release : 2019-10-18
  • ISBN : 3030337782
  • Pages : 555 pages

Download or read book Discovery Science written by Petra Kralj Novak and published by Springer Nature. This book was released on 2019-10-18 with total page 555 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 22nd International Conference on Discovery Science, DS 2019, held in Split, Coratia, in October 2019. The 21 full and 19 short papers presented together with 3 abstracts of invited talks in this volume were carefully reviewed and selected from 63 submissions. The scope of the conference includes the development and analysis of methods for discovering scientific knowledge, coming from machine learning, data mining, intelligent data analysis, big data analysis as well as their application in various scientific domains. The papers are organized in the following topical sections: Advanced Machine Learning; Applications; Data and Knowledge Representation; Feature Importance; Interpretable Machine Learning; Networks; Pattern Discovery; and Time Series.

Book Foundations of Rule Learning

    Book Details:
  • Author : Johannes Fürnkranz
  • Publisher : Springer Science & Business Media
  • Release : 2012-11-06
  • ISBN : 3540751971
  • Pages : 345 pages

Download or read book Foundations of Rule Learning written by Johannes Fürnkranz and published by Springer Science & Business Media. This book was released on 2012-11-06 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt: Rules – the clearest, most explored and best understood form of knowledge representation – are particularly important for data mining, as they offer the best tradeoff between human and machine understandability. This book presents the fundamentals of rule learning as investigated in classical machine learning and modern data mining. It introduces a feature-based view, as a unifying framework for propositional and relational rule learning, thus bridging the gap between attribute-value learning and inductive logic programming, and providing complete coverage of most important elements of rule learning. The book can be used as a textbook for teaching machine learning, as well as a comprehensive reference to research in the field of inductive rule learning. As such, it targets students, researchers and developers of rule learning algorithms, presenting the fundamental rule learning concepts in sufficient breadth and depth to enable the reader to understand, develop and apply rule learning techniques to real-world data.

Book Discovery Science

Download or read book Discovery Science written by and published by . This book was released on 2001 with total page 524 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Discovery Science

    Book Details:
  • Author : Klaus P. Jantke
  • Publisher : Springer
  • Release : 2003-06-30
  • ISBN : 3540456503
  • Pages : 510 pages

Download or read book Discovery Science written by Klaus P. Jantke and published by Springer. This book was released on 2003-06-30 with total page 510 pages. Available in PDF, EPUB and Kindle. Book excerpt: These are the conference proceedings of the 4th International Conference on Discovery Science (DS 2001). Although discovery is naturally ubiquitous in s- ence, and scientific discovery itself has been subject to scientific investigation for centuries, the term Discovery Science is comparably new. It came up in conn- tion with the Japanese Discovery Science project (cf. Arikawa's invited lecture on The Discovery Science Project in Japan in the present volume) some time during the last few years. Setsuo Arikawa is the father in spirit of the Discovery Science conference series. He led the above mentioned project, and he is currently serving as the chairman of the international steering committee for the Discovery Science c- ference series. The other members of this board are currently (in alphabetical order) Klaus P. Jantke, Masahiko Sato, Ayumi Shinohara, Carl H. Smith, and Thomas Zeugmann. Colleagues and friends from all over the world took the opportunity of me- ing for this conference to celebrate Arikawa's 60th birthday and to pay tribute to his manifold contributions to science, in general, and to Learning Theory and Discovery Science, in particular. Algorithmic Learning Theory (ALT, for short) is another conference series initiated by Setsuo Arikawa in Japan in 1990. In 1994, it amalgamated with the conference series on Analogical and Inductive Inference (AII), when ALT was held outside of Japan for the first time.

Book Proceedings of the Fourteenth Annual Conference of the Cognitive Science Society

Download or read book Proceedings of the Fourteenth Annual Conference of the Cognitive Science Society written by Cognitive Science Society (US) Conference and published by Psychology Press. This book was released on 2014-05-12 with total page 1204 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume features the complete text of all regular papers, posters, and summaries of symposia presented at the 14th annual meeting of the Cognitive Science Society.

Book Proceedings of the Fifteenth Annual Conference of the Cognitive Science Society

Download or read book Proceedings of the Fifteenth Annual Conference of the Cognitive Science Society written by Science Society Cognitive, Con and published by Psychology Press. This book was released on 1993 with total page 1080 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume features the complete text of all regular papers, posters, and summaries of symposia presented at the 15th annual meeting of the Cognitive Science Society.

Book Multistrategy Learning

    Book Details:
  • Author : Ryszard S. Michalski
  • Publisher : Springer Science & Business Media
  • Release : 2012-12-06
  • ISBN : 1461532027
  • Pages : 156 pages

Download or read book Multistrategy Learning written by Ryszard S. Michalski and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt: Most machine learning research has been concerned with the development of systems that implememnt one type of inference within a single representational paradigm. Such systems, which can be called monostrategy learning systems, include those for empirical induction of decision trees or rules, explanation-based generalization, neural net learning from examples, genetic algorithm-based learning, and others. Monostrategy learning systems can be very effective and useful if learning problems to which they are applied are sufficiently narrowly defined. Many real-world applications, however, pose learning problems that go beyond the capability of monostrategy learning methods. In view of this, recent years have witnessed a growing interest in developing multistrategy systems, which integrate two or more inference types and/or paradigms within one learning system. Such multistrategy systems take advantage of the complementarity of different inference types or representational mechanisms. Therefore, they have a potential to be more versatile and more powerful than monostrategy systems. On the other hand, due to their greater complexity, their development is significantly more difficult and represents a new great challenge to the machine learning community. Multistrategy Learning contains contributions characteristic of the current research in this area.

Book Rough Set Methods and Applications

Download or read book Rough Set Methods and Applications written by Lech Polkowski and published by Physica. This book was released on 2012-10-07 with total page 679 pages. Available in PDF, EPUB and Kindle. Book excerpt: Rough set approach to reasoning under uncertainty is based on inducing knowledge representation from data under constraints expressed by discernibility or, more generally, similarity of objects. Knowledge derived by this approach consists of reducts, decision or association rules, dependencies, templates, or classifiers. This monograph presents the state of the art of this area. The reader will find here a deep theoretical discussion of relevant notions and ideas as well as rich inventory of algorithmic and heuristic tools for knowledge discovery by rough set methods. An extensive bibliography will help the reader to get an acquaintance with this rapidly growing area of research.

Book Advances in Artificial Intelligence

Download or read book Advances in Artificial Intelligence written by Howard J. Hamilton and published by Springer. This book was released on 2003-06-26 with total page 462 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 13th Biennial Conference of the Canadian Society for Computational Studies of Intelligence, AI 2000, held in Montreal, Quebec, Canada, in May 2000. The 25 revised full papers presented together with 12 10-page posters were carefully reviewed and selected from more than 70 submissions. The papers are organized in topical sections on games and constraint satisfaction; natural language processing; knowledge representation; AI applications; machine learning and data mining; planning, theorem proving, and artificial life; and neural networks.

Book Rough Sets  Fuzzy Sets and Knowledge Discovery

Download or read book Rough Sets Fuzzy Sets and Knowledge Discovery written by Wojciech P. Ziarko and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 486 pages. Available in PDF, EPUB and Kindle. Book excerpt: The objective of this book is two-fold. Firstly, it is aimed at bringing to gether key research articles concerned with methodologies for knowledge discovery in databases and their applications. Secondly, it also contains articles discussing fundamentals of rough sets and their relationship to fuzzy sets, machine learning, management of uncertainty and systems of logic for formal reasoning about knowledge. Applications of rough sets in different areas such as medicine, logic design, image processing and expert systems are also represented. The articles included in the book are based on selected papers presented at the International Workshop on Rough Sets and Knowledge Discovery held in Banff, Canada in 1993. The primary methodological approach emphasized in the book is the mathematical theory of rough sets, a relatively new branch of mathematics concerned with the modeling and analysis of classification problems with imprecise, uncertain, or incomplete information. The methods of the theory of rough sets have applications in many sub-areas of artificial intelligence including knowledge discovery, machine learning, formal reasoning in the presence of uncertainty, knowledge acquisition, and others. This spectrum of applications is reflected in this book where articles, although centered around knowledge discovery problems, touch a number of related issues. The book is intended to provide an important reference material for students, researchers, and developers working in the areas of knowledge discovery, machine learning, reasoning with uncertainty, adaptive expert systems, and pattern classification.