Machine Discovery PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Machine Discovery PDF full book. Access full book title Machine Discovery by Jan Zytkow. Download full books in PDF and EPUB format.
Author: Jan Zytkow
Publisher: Springer Science & Business Media
ISBN: 9401721246
Category : Psychology
Languages : en
Pages : 229
Get Book Here
Book Description
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.
Author: Jan Zytkow
Publisher: Springer Science & Business Media
ISBN: 9401721246
Category : Psychology
Languages : en
Pages : 229
Get Book Here
Book Description
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.
Author: Peter Edwards
Publisher: Morgan Kaufmann
ISBN: 1483298531
Category : Computers
Languages : en
Pages : 497
Get Book Here
Book Description
Machine Learning Proceedings 1992
Author:
Publisher:
ISBN:
Category : Aeronautics
Languages : en
Pages : 1572
Get Book Here
Book Description
Author: Ashwin Ram
Publisher: Routledge
ISBN: 1317729269
Category : Psychology
Languages : en
Pages : 1014
Get Book Here
Book Description
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.
Author: David L Dowe
Publisher: World Scientific
ISBN: 9814547263
Category :
Languages : en
Pages : 423
Get Book Here
Book Description
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.).
Author: Petra Kralj Novak
Publisher: Springer Nature
ISBN: 3030337782
Category : Computers
Languages : en
Pages : 555
Get Book Here
Book Description
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.
Author: Johannes Fürnkranz
Publisher: Springer Science & Business Media
ISBN: 3540751971
Category : Computers
Languages : en
Pages : 345
Get Book Here
Book Description
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.
Author:
Publisher:
ISBN:
Category : Computer science
Languages : en
Pages : 524
Get Book Here
Book Description
Author: Cognitive Science Society (US) Conference
Publisher: Psychology Press
ISBN: 1317781619
Category : Psychology
Languages : en
Pages : 1204
Get Book Here
Book Description
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.
Author: Klaus P. Jantke
Publisher: Springer
ISBN: 3540456503
Category : Computers
Languages : en
Pages : 510
Get Book Here
Book Description
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.
