Advanced Topics in Artificial Intelligence

1. Front Matter

   Pages I-XV

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2. Machine Learning I

   1. Generating Rule Sets from Model Trees

      • Geoffrey Holmes, Mark Hall, Eibe Prank

      Pages 1-12

   2. Classifying and Learning Cricket Shots Using Camera Motion

      • Mihai Lazarescu, Svetha Venkatesh, Geoff West

      Pages 13-23

   3. Unsupervised Learning in Metagame

      • Graham E. Farr, David R. Powell

      Pages 24-35

3. Neural Nets

   1. A Neural Networks Based Approach for Fast Mining Characteristic Rules

      • Monzurur Rahman, Xinghuo Yu, Bala Srinivasan

      Pages 36-47

   2. FANRE: A Fast Adaptive Neural Regression Estimator

      • Zhihua Zhou, Shifu Chen, Zhaoqian Chen

      Pages 48-59

   3. Neural Networks for Defuzification of Fuzzy Rules: An Application in Macroeconomic Forecasting

      • Raouf Veliev, Alex Rubinov, Andrew Stranieri

      Pages 60-71

4. Knowledge Representation I

   1. Semantic Integration of Databases Using Linguistic Knowledge

      • Jeong-Oog Lee, Doo-Kwon Baik

      Pages 72-83

   2. Representing ‘Just Invalid’ Knowledge

      • John Debenham

      Pages 84-95

   3. Maximising Expected Utility for Behaviour Arbitration

      • Julio K. Rosenblatt

      Pages 96-108

5. Natural Language

   1. Generating Natural Language Descriptions of Project Plans

      • Margaret Wasko, Robert Dale

      Pages 109-121

   2. Categorizing Unknown Words: A Decision Tree-Based Misspelling Identifier

      • Janine Toole

      Pages 122-133

   3. Sync/Trans: Simultaneous Machine Interpretation between English and Japanese

      • Shigeki Matsubara, Katsuhiko Toyama, Yasuyoshi Inagaki

      Pages 134-143

6. Belief Revision

   1. Minimal Belief Change and Pareto-Optimality

      • Oliver Schulte

      Pages 144-155

   2. Basic Infobase Change

      • Thomas Meyer

      Pages 156-167

   3. A Framework for Multi-Agent Belief Revision Part I: The Role of Ontology

      • Wei Liu, Mary-Anne Williams

      Pages 168-179

7. Adaptive Algorithms

   1. Genetic Programming for Multiple Class Object Detection

      • Mengjie Zhang, Victor Ciesielski

      Pages 180-192

   2. A Simulated Annealing-Based Learning Algorithm for Boolean DNF

      • Andreas Albrecht, Kathleen Steinhöfel

      Pages 193-204

   3. Mutant: A Genetic Learning System

      • Stéphane Calderoni, Pierre Marcenac

      Pages 205-217

8. Automated Reasoning

   1. Computing Least Common Subsumers in Expressive Description Logics

      • Thomas Mantay

      Pages 218-230

The 12th Australian Joint Conference on Artificial Intelligence (AI'QQ) held in Sydney, Australia, 6-10 December 1999, is the latest in a series of annual re­ gional meetings at which advances in artificial intelligence are reported. This series now attracts many international papers, and indeed the constitution of the program committee reflects this geographical diversity. Besides the usual tutorials and workshops, this year the conference included a companion sympo­ sium at which papers on industrial appUcations were presented. The symposium papers have been published in a separate volume edited by Eric Tsui. Ar99 is organized by the University of New South Wales, and sponsored by the Aus­ tralian Computer Society, the Commonwealth Scientific and Industrial Research Organisation (CSIRO), Computer Sciences Corporation, the KRRU group at Griffith University, the Australian Artificial Intelligence Institute, and Neuron- Works Ltd. Ar99 received over 120 conference paper submissions, of which about o- third were from outside Australia. Prom these, 39 were accepted for regular presentation, and a further 15 for poster display. These proceedings contain the full regular papers and extended summaries of the poster papers. All papers were refereed, mostly by two or three reviewers selected by members of the program committee, and a list of these reviewers appears later. The technical program comprised two days of workshops and tutorials, fol­ lowed by three days of conference and symposium plenary and paper sessions.

• Artificial intelligence
• adaptive systems
• agent systems
• classification
• heuristics
• intelligence
• intelligent agents
• knowledge processing
• knowledge representation
• learning
• machine learning
• natural language
• natural language processing
• neural computing
• ontology

• School of Computer Science and Engineering, University of New South Wales, Sydney, Australia

  Norman Foo

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