Tools in Artificial Intelligence Tools in Arti f i ci al Intellige nce Edited by Paula Fritzsche I-Tech IV Published by In-Teh In-Teh is Croatian branch of I-Tech Education and Publishing KG, Vienna, Austria. Abstracting and non-profit use of the material is permitted with credit to the source. Statements and opinions expressed in the chapters are these of the individual contributors and not necessarily those of the editors or publisher. No responsibility is accepted for the accuracy of information contained in the published articles. Publisher assumes no responsibility liability for any damage or injury to persons or property arising out of the use of any materials, instructions, methods or ideas contained inside. After this work has been published by the In-Teh, authors have the right to republish it, in whole or part, in any publication of which they are an author or editor, and the make other personal use of the work. © 2008 In-teh www.in-teh.org Additional copies can be obtained from: publication@ars-journal.com First published August 2008 Printed in Croatia A catalogue record for this book is available from the University Library Rijeka under no. 111220071 Tools in Artificial Intelligence, Edited by Paula Fritzsche p. cm. ISBN 978-953-7619-03-9 1. Artificial Intelligence. 2. Tools. I. Paula Fritzsche Preface Artificial Intelligence (AI) is often referred to as a branch of science which deals with helping machines find solutions to complex problems in a more human-like fashion. It is generally associated with Computer Science, but it has many important links with other fields such as Maths, Psychology, Cognition, Biology and Philosophy. The AI success is due to its technology has diffused into everyday life. Neural networks, fuzzy controls, decision trees and rule-based systems are already in our mobile phones, washing machines and business applications. The book “Tools in Artificial Intelligence” offers in 27 chapters a collection of all the tech- nical aspects of specifying, developing, and evaluating the theoretical underpinnings and applied mechanisms of AI tools. Topics covered include neural networks, fuzzy controls, decision trees, rule-based systems, data mining, genetic algorithm and agent systems, among many others. The goal of this book is to show some potential applications and give a partial picture of the current state-of-the-art of AI. Also, it is useful to inspire some future research ideas by identifying potential research directions. It is dedicated to students, researchers and practi- tioners in this area or in related fields. Editor Paula Fritzsche Computer Architecture and Operating Systems Department University Autonoma of Barcelona Spain e-mail: paula.fritzsche@caos.uab.es VII Contents Preface V 1. Computational Intelligence in Software Cost Estimation: Evolving Conditional Sets of Effort Value Ranges 001 Efi Papatheocharous and Andreas S. Andreou 2. Towards Intelligible Query Processing in Relevance Feedback-Based Image Retrieval Systems 021 Belkhatir Mohammed 3. GNGS: An Artificial Intelligent Tool for Generating and Analyzing Gene Networks from Microarray Data 035 Austin H. Chen and Ching-Heng Lin 4. Preferences over Objects, Sets and Sequences 049 Sandra de Amo and Arnaud Giacometti 5. Competency-based Learning Object Sequencing using Particle Swarms 077 Luis de Marcos, Carmen Pages, José Javier Martínez and José Antonio Gutiérrez 6. Image Thresholding of Historical Documents Based on Genetic Algorithms 093 Carmelo Bastos Filho, Carlos Alexandre Mello, Júlio Andrade, Marília Lima, Wellington dos Santos, Adriano Oliveira and Davi Falcão 7. Segmentation of Greek Texts by Dynamic Programming 101 Pavlina Fragkou, Athanassios Kehagias and Vassilios Petridis 8. Applying Artificial Intelligence to Predict the Performance of Data-dependent Applications 121 Paula Fritzsche, Dolores Rexachs and Emilio Luque 9. Agent Systems in Software Engineering 139 Vasilios Lazarou and Spyridon Gardikiotis 10. A Joint Probability Data Association Filter Algorithm for Multiple Robot Tracking Problems 163 Aliakbar Gorji Daronkolaei, Vahid Nazari, Mohammad Bagher Menhaj, and Saeed Shiry 11. Symbiotic Evolution of Rule Based Classifiers 187 Ramin Halavati and Saeed Bagheri Shouraki VIII 12. A Multiagent Method to Design Open Embedded Complex Systems 205 Jamont Jean-Paul and Occello Michel 13. Content-based Image Retrieval Using Constrained Independent Component Analysis: Facial Image Retrieval Based on Compound Queries 223 Tae-Seong Kim and Bilal Ahmed 14. Text Classification Aided by Clustering: a Literature Review 233 Antonia Kyriakopoulou 15. A Review of Past and Future Trends in Perceptual Anchoring. 253 Silvia Coradeschi and Amy Loutfi 16. A Cognitive Vision Approach to Image Segmentation 265 Vincent Martin and Monique Thonnat 17. An Introduction to the Problem of Mapping in Dynamic Environments 295 Nikos C. Mitsou and Costas S. Tzafestas 18. Inductive Conformal Prediction: Theory and Application to Neural Networks 315 Harris Papadopoulos 19. Robust Classification of Texture Images using Distributional-based Multivariate Analysis 331 Vasileios K. Pothos, Christos Theoharatos, George Economou and Spiros Fotopoulos 20. Recent Developments in Bit-Parallel Algorithms 349 Pablo San Segundo, Diego Rodríguez-Losada and Claudio Rossi 21. Multi-Sensor Fusion for Mono and Multi-Vehicle Localization using Bayesian Network 369 C. Smaili, M. E. El Najjar, F. Charpillet and C. Rose 22. On the Definition of a Standard Language for Modelling Constraint Satisfaction Problems 387 Ricardo Soto, Laurent Granvilliers 23. Software Component Clustering and Retrieval: An Entropy-based Fuzzy k-Modes Methodology 399 Constantinos Stylianou and Andreas S. Andreou 24. An Agent-Based System to Minimize Earthquake-Induced Damages 421 Yoshiya Takeuchi, Takashi Kokawa, Ryota Sakamoto, Hitoshi Ogawa and Victor V. Kryssanov IX 25. A Methodology for the Extraction of Readers Emotional State Triggered from Text Typography 439 Dimitrios Tsonos and Georgios Kouroupetroglou 26. Granule Based Inter-transaction Association Rule Mining 455 Wanzhong Yang, Yuefeng Li and Yue Xu 27. Countering Good Word Attacks on Statistical Spam Filters with Instance Differentiation and Multiple Instance Learning 473 Yan Zhou, Zach Jorgensen and Meador Inge [...]... estimation involves the overall assessment of these parameters, even though for the majority of the projects, the most dominant and popular metric is the effort cost, typically measured in person-months Recent attempts have investigated the potential of employing Artificial Intelligence- oriented methods to forecast software development effort, usually utilising publicly available 2 Tools in Artificial Intelligence. .. needed towards defining which measures, or combination of measures, is more appropriate for the 4 Tools in Artificial Intelligence particular problem In (Dolado, 2001) GP evolving tree structures, which represent software cost estimation equations, is investigated in relation to other classical equations, like the linear, power, quadratic, etc Different datasets were used in that study yielding diverse results,... attributes with high deviations in their 8 Tools in Artificial Intelligence values and measurement Therefore, this led us to examine smaller, more compact, homogeneous and free from outlier subsets In fact, we managed to extract three final datasets which we used in our final series of experiments The first dataset (DS-1) contained the main attributes suggested by Function Point Analysis (FPA) to provide... conditional set S as an individual in the population of our GA, which will be thoroughly explained in the next section as part of the proposed methodology We use equations (3) and (4) to describe conditional sets representing cost attributes, or to be more precise, cost metrics What we are interested in is the definition of a set of software projects, 6 Tools in Artificial Intelligence M, the elements... Models based on Function Points Analysis (FPA) (Albrecht & Gaffney, 1983) mainly involve identifying and classifying the major system components such as external inputs, external outputs, logical internal files, external interface files and external inquiries The classification is based on their characterization as ‘simple’, ‘average’ or ‘complex’, depending on the number of interacting data elements and... that are domainindependent, and aim to find approximated solutions in complex optimization and search problems (Holland, 1992) They achieve this by pruning a population of individuals based on the Darwinian principle of reproduction and ‘survival of the fittest’ (Koza, 1992) The fitness of each individual is based on the quality of the simulated individual in the environment of the problem investigated... top best performing individuals are copied in the next generation and thus, rapidly increase the performance of the algorithm 2.2.2 Crossover; two or more individuals are randomly chosen from the population and parts of their genetic information are recombined to produce new individuals Crossover with two individuals takes place either by exchanging their ranges at the crossover point (inter-crossover)... satisfying Ci (OR case) Additionally, the evaluation rewards individuals whose difference among the lower and upper range is minimal Finally, wi in equations (9) and (10) is a weighting factor corresponding to the significance given by the estimator to a certain cost attribute The purpose of the fitness functions is to define the appropriateness of the value ranges produced within each individual according... Genetic Programming to Software Quality Prediction Computational Intelligence in Software Engineering, Series on Advances in Fuzzy Systems – Applications and Theory, Vol 16, pp 176-195, World Scientific, Singapore Koza, J.R (1992) Genetic Programming: On the Programming of Computers by Means of Natural Selection, MIT Press, Massachusetts Lederer, A.L & Prasad, J (1992) Nine Management Guidelines for Better... since, as shown in [Hollink 04], taking into account aspects related to the image content is of prime importance for efficient retrieval Also, users are more skilled in defining their information needs using language-based descriptors and would therefore rather be given the possibility to differentiate between red roses and red cars In order to overcome the semantic gap, a class of frameworks within . have investigated the potential of employing Artificial Intelligence- oriented methods to forecast software development effort, usually utilising publicly available Tools in Artificial Intelligence. in our mobile phones, washing machines and business applications. The book Tools in Artificial Intelligence offers in 27 chapters a collection of all the tech- nical aspects of specifying,. 111220071 Tools in Artificial Intelligence, Edited by Paula Fritzsche p. cm. ISBN 978-953-7619-03-9 1. Artificial Intelligence. 2. Tools. I. Paula Fritzsche Preface Artificial