Frans Coenen University of Liverpool, UK This volume comprises the refereed technical papers presented at AI2003, the Twenty third SGAI International Conference on the theory, practice and application of Artificial Intelligence, held in Cambridge in December 2003. The conference was organised by SGAI, the British Computer Society Specialist Group on Artificial Intelligence (previously known as SGES). The papers in this volume present new and innovative developments in the field, divided into sections on Machine Learning, Knowledge Representation and Reasoning, Knowledge Acquisition, Constraint Satisfaction, Scheduling and Natural Language Processing. This year's prize for the best refereed technical paper was won by a paper entitled An Improved Hybrid Genetic Algorithm: New Results for the Quadratic Assignment Problem by A. Misevicius (Department of Practical Informatics, Kaunas University of Technology, Lithuania). SGAI gratefully acknowledges the long-term sponsorship of Hewlett-Packard Laboratories (Bristol) for this prize, which goes back to the 1980s. This is the twentieth volume in the Research and Development series. The Application Stream papers are published as a companion volume under the title Applications and Innovations in Intelligent Systems XI. On behalf of the conference organising committee I should like to thank all those who contributed to the organisation of this year's technical programme, in particular the programme committee members, the referees and our administrator Fiona Hartree and Linsay Turbert.
- Verlag: Springer, Berlin
- Softcover reprint of the original 1st ed. 2004
- Seitenzahl: 408
- Ausstattung/Bilder: Softcover reprint of the original 1st ed. 2004. 2004. xi, 395 S. 44 SW-Abb. 235 mm
- Abmessung: 235mm x 155mm x 21mm
- Gewicht: 581g
- ISBN-13: 9781852337803
- ISBN-10: 185233780X
- Best.Nr.: 22907127
Best Refereed Technical Paper.- An Improved Hybrid Genetic Algorithm: New Results for the Quadratic Assignment Problem.- Session 1A: Algorithms And A1 (Gas, Hidden Markov Models, Simulated Annealing And Perceptrons.- Adaptive Mutation Using Statistics Mechanism for Genetic Algorithms.- Off-line Recognition of Handwritten Arabic Words Using Multiple Hidden Markov Models.- On a New Stepwidth Adaptation Scheme for Simulated Annealing and its Practical Application.- An Approximate Algorithm for Reverse Engineering of Multi-layer Perceptrons.- Session 18: Constraint Programming I.- A Theoretical Framework for Tradeoff Generation using Soft Constraints.- Maximum Partial Assignments for Over-Constrained Problems.- Escaping Local Optima in Multi-Agent Oriented Constraint Satisfaction.- Constraint Acquisition as Semi-Automatic Modeling.- Session 2A: Knowledge Discovery In Data (Association Rules, Clustering And Classification).- Strategies for Partitioning Data in Association Rule Mining.- A Self-Organising Hybrid Model for Dynamic Text Clustering.- Polynomial-Fuzzy Decision Tree Structures for Classifying Medical Data.- A Comparison of Generic Machine Learning Algorithms for Image Classification.- Session 2B: Constraint Programming 2.- Turtle: A Constraint Imperative Programming Language.- Symmetry Breaking in Soft CSPs.- How to Classify Hard and Soft Constraints in Non-binary Constraint Satisfaction Problems.- Lightweight MAC Algorithms.- Session 3: Spatio-Temporal Reasoning And Machine Learning.- SPARQS: Automatic Reasoning in Qualitative Space.- Incorporating Reactive Learning Behaviour into a Mini-robot Platform.- An Approach to Instance Reduction in Supervised Learning.- Session 4: Knowledge Organisation, Representation, V&V and Refinement.- Optimal Decision Explanation by Extracting Regularity Patterns.- Model-based Planning in Physical domains using SetGraphs.- Quality Checking of Medical Guidelines through Logical Abduction.- Constraint Relaxation Techniques to Aid the Reuse of Knowledge Bases and Problem Solvers.- Session 5: Multi-Agent Systems And Recommender Systems.- Adaptive Brokering in Agent-Mediated Electronic Commerce.- CONOISE: Agent-Based Formation of Virtual Organisations.- I-SPY â€” Anonymous, Community-Based Personalization by Collaborative Meta-Search.- Balancing User Satisfaction and Cognitive Load in Coverage-Optimised Retrieval.