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Research and development in intelligent systems XXVI : incorporating applications and innovations in intelligent systems XVII
Bramer M., Ellis R., Petridis M., Springer Publishing Company, Incorporated, New York, NY, 2009. 504 pp. Type: Book (978-1-848829-82-4)
Date Reviewed: Apr 22 2010

Papers and posters presented at the 29th SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, the last conference in an established series held annually in Cambridge, UK, are collected in this book. It presents a wide range of research topics. As events rooted in a central technology, it is interesting to also view the papers presented as an indication of the consolidation of approaches, the emergence of new topics, and the disappearance of themes. If we compare the topics indicated in the “Call for Papers”--which has been quite stable in the last few editions--with the topics covered by the accepted papers, the hot themes emerge.

The topics suggested in the technical stream are: knowledge engineering; the semantic Web; constraint satisfaction; intelligent agents; machine learning; model-based reasoning; verification and validation of artificial intelligence (AI) systems; natural language understanding; speech-enabled systems; case-based reasoning; neural networks; genetic algorithms; data mining and knowledge discovery in databases; knowledge representation, inference, and reasoning; robotics and pervasive computing; qualitative and temporal reasoning; knowledge management; and AI languages and environments.

The technical stream has five sections, each containing three or four papers:

  • Knowledge discovery and data mining (with papers on text classification, temporal data, a review recommender, and hypothesis generation from anomalous responses);
  • Reasoning (with papers on dual rationality for agents, tables for qualitative spatial reasoning, influence diagrams, and logical formalization of analogical reasoning);
  • Data mining and machine learning (with papers on clustering for genetic regulatory networks, parallel rule induction, the extension of univariate kernels, and modeling wavelets);
  • Optimization and planning (with papers on group optimization, global optimization metaheuristics, population-based optimization, and plan execution language--the only robotics paper); and
  • Knowledge acquisition and evolutionary computation (with papers on real-time strategy games, crossover strategy in genetic algorithms (GAs), and chunking natural language text using GAs).

The short papers (presented as posters) are about multiagent learning, subclass partition information in binary classifiers, temporal reasoning formalism, arc consistency, feature subset selection, and e-manufacturing.

Some topics, such as case-based reasoning, speech, natural language, and robotics, are very poorly covered. However, the emphasis on integration between data mining and statistical models and the refinement of classical algorithms are relevant.

In the application stream, the case studies presented describe the application of AI to real-world problems for scheduling, design, commerce, and an affective user interface.

The award-winning papers, one in each stream, are: “Coping with noisy search experiences,” by Champin, Briggs, Coyle, and Smyth, which analyzes a recommendation system, showing how a classifier can deal with the noisy data obtained from users, and “Corpus callosum MR image classification,” by Elsayed, Coenen, Jiang, Garcia-Finana, and Sluming, which presents a system to classify magnetic resonance (MR) images according to the nature of a brain structure (corpus callosum); after feature extraction, they build a quadtree representation and apply data mining, obtaining a high level of accuracy.

Most of the papers have a quite formal approach. A few also have a relevant application interest. They are all presented to professionals in AI, so the book should appeal to AI scholars and practitioners.

Reviewer:  G. Gini Review #: CR137928 (1103-0263)
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