MACHINE LEARNING Editor-in-Chief (+deputy) Thomas G. Dietterich Oregon State University and Arris Pharmaceutical, Inc. Edited by Ken de Jong George Mason University and NRL David Haussler University of California, Santa Cruz Dennis Kibler University of California, Irvine Steven Minton NASA Ames Research Center Leonard Pitt University of Illinois Bruce Porter University of Texas, Austin Richard Sutton GTE Laboratories Paul E. Utgoff University of Massachusetts, Amherst, MA, USA J.R. Quinlan University of Sydney AIMS AND SCOPE Machine Learning is an international forum for research on computational approaches to learning. The journal publishes articles reporting substantive research results on a wide range of learning methods applied to a variety of task domains, including but not limited to: Methods Inductive learning methods; Explanation-based learning; Genetic algorithms; Analogy and case-based methods; Connectionist techniques; Automated knowledge acquisition; Learning from instruction. Task Domains Classification and recognition; Problem solving and planning; Reasoning and inference; Natural language processing; Design and diagnosis; Vision and speech perception; Robotics and motor control. The ideal paper will make a theoretical contribution supported by a computer implementation. In addition to carefully describing the learning component, it should also discuss knowledge representation and performance assumptions. The article should carefully evaluate the approach through empirical studies, theoretical analysis, or comparison to psychological phenomena, and should discuss its relation to other work in machine learning. Variation from this prototype, such as critical reviews of existing work, will be considered provided they make a clear contribution to the field. Machine Learning is abstracted/indexed in: ISI: Current Contents: Engineering, Technology and Applied Science; ISI: Compumath Citation Index; Artificial Intelligence Abstracts; Computer and Information Systems Abstracts; ACM Guide to Computing Literature, ACM Computing Reviews; INSPEC Information Services; COMPENDEX lus database; Engineering Index; ISI: Scisearch; ISI: Automatic Subject Citation Alert, Sociological Abstracts. INFORMATION FOR AUTHORS Machine Learning publishes articles on the mechanisms through which intelligent systems improve their performance over time. We invite authors to submit papers describing computational approaches to any aspect of learning. We especially encourage models of human learning, theoretical analyses of learning tasks, and empirical studies of learning algorithms. SUBMISSION. Authors should submit six (6) copies of papers as indicated: Five (5) hard copies to: Mrs. Karen Cullen MACHINE LEARNING Kluwer Academic Publishers 101 Philip Drive Assinippi Park Norwell, MA 02061 One (1) hard copy to: Professor Thomas G. Dietterich Department of Computer Science Dearborn Hall 303 Oregon State University Corvallis, OR 97331-3202 Also, please send technical and methodological notes (i.e., very short papers for rapid review) to Mrs. Karen Cullen at the above address. Papers will be evaluated based on the results set forth in the manuscript and not on work in progress. Book Reviews: Please send two (2) copies of books to be considered for review to Professor Alberto Segre, Department of Computer Science, Upson Hall, Cornell University, Ithaca, NY 14853-7501. TITLE PAGE. Please list your name, affiliation, and complete address on the title paper, providing a daytime telephone number, and an electronic mail address if available. Include a brief, one- paragraph abstract of 100-200 words and a list of six or fewer key words. Also include a shortened version of your title for use on page headings; identify this as the running head. TEXT. Begin the text on a new page following the title page. Manuscripts should be typewritten on 8 1/2 x 11 in. paper, single-sided and double-spaced, with papers numbered consecutively. Papers should be 8,000 to 12,000 words in length, with full-page figures counting for 400 words. Use footnotes sparingly, indicating them by consecutive numbers in the text. Include acknowledgements in a separate section at the end of the text. REFERENCES. Authors should follow the APA Publication Manual for both the text and the reference list, with two exceptions: (a) do not cite the page numbers of any book, including chapters in edited volumes; (b) use the same format for unpublished references as for published ones. Examples for journals, chapters, and proceedings are given below: Laird, J.E. Rosenbloom, P.S., & Newell, A (1986.) SOAR: The anatomy of a general learning mechanism. Machine Learning, 1, 11- 46. Quinlan, J.R. (1986.) The effect of noise on concept learning. In R.S. Michalski, J.G. Carbonell, & T.M. Mitchell (Eds.), Machine Learning: An artificial approach (Vol.2). San Mateo, CA: Morgan Kaufmann. Schlimmer, J.C., & Fisher, D.H. (1986). A case study of incremental concept induction. Proceedings of the Fifth National Conference on Artificial Intelligence (pp. 496-501). Philadelphia, PA: Morgan Kaufmann. FIGURES AND TABLES. Mention each figure and table in the text and number them consecutively using Arabic numerals. Embed them in the text if possible to ease the reviewing process. Figures should contain graphical material, whereas tables should contain tabular and typeset material. Include a brief title above each table and a caption below each figure. SPELLING AND TERMINOLOGY. Authors should employ technical terms with care, using existing terms when defined by earlier authors and carefully specifying the sense in which they intend ambiguous terms. Please keep abbreviations to a minimum. American spelling is preferred to British spelling. REPRINTS AND PAGE CHARGES. Authors of published papers will be provided with 50 reprints free of charge. No page charges will be levied. ************************************ * SUBSCRIPTION INFORMATION: * ************************************ ***Ordering options: 1. You may order through your usual ordering agent, or 2. 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