The 7th Annual European Symposium on Algorithms (ESA ’99) is held in Prague, Czech Republic, July 16-18, 1999. This continued the tradition of the meetings which were held in – 1993 Bad Honnef (Germany) – 1994 Utrecht (Netherlands) – 1995 Corfu (Greece) – 1996 Barcelona (Spain) – 1997 Graz (Austria) – 1998 Venice (Italy) (The proceedingsof previousESA meetings were publishedas Springer LNCS v- umes 726, 855, 979, 1136, 1284, 1461.) In the short time of its history ESA (like its sister meeting SODA) has become a popular and respected meeting. The call for papers stated that the “Symposium covers research in the use, design, and analysis of ef?cient algorithms and data structures as it is carried out in c- puter science, discrete applied mathematics and mathematical programming. Papers are solicited describing original results in all areas of algorithmic research, including but not limited to: Approximation Algorithms; Combinatorial Optimization; Compu- tional Biology; Computational Geometry; Databases and Information Retrieval; Graph and Network Algorithms; Machine Learning; Number Theory and Computer Algebra; On-line Algorithms; Pattern Matching and Data Compression; Symbolic Computation.

This book presents the foundations of phylogeny estimation and technical material enabling researchers to develop improved computational methods.

Computational Intelligence (CI) is a recently emerging area in fundamental and applied research, exploiting a number of advanced information processing technologies that mainly embody neural networks, fuzzy logic and evolutionary computation. With a major concern to exploiting the tolerance for imperfection, uncertainty, and partial truth to achieve tractability, robustness and low solution cost, it becomes evident that composing methods of CI should be working concurrently rather than separately. It is this conviction that research on the synergism of CI paradigms has experienced significant growth in the last decade with some areas nearing maturity while many others remaining unresolved. This book systematically summarizes the latest findings and sheds light on the respective fields that might lead to future breakthroughs. Contents: A Quest for Granular Computing and Logic Processing (W Pedrycz); Abstraction and Linguistic Analysis of Conventional Numerical Dynamic Systems (F-Y Wang); Slicing: A Distributed Learning Approach (S A Eschrich & L O Hall); Marginal Learning Algorithms in Statistical Machine Learning (Q Tao & J Wang); Constraint Handling in Genetic Algorithm for Optimization (G G Yen); Hybrid PSO-EA Algorithm for Training Feedforward and Recurrent Neural Networks for Challenging Problems (X Cai et al.); Modular Wavelet-Fuzzy Networks (Y Lin & F-Y Wang); Ant Colony Algorithms: The State-of-the-Art (J Zhang et al.); Motif Discoveries in DNA and Protein Sequences Using Self-Organizing Neural Networks (D Liu & X Xiong); Computational Complexities of Combinatorial Problems with Applications to Reverse Engineering of Biological Networks (P Berman et al.); Advances in Fingerprint Recognition Algorithms with Application (J Tian et al.); Adaptation and Predictive Control Observed in Neuromuscular Control Systems (J He); Robust Adaptive Approximation Based Backstepping via Localized Adaptive Bounding (Y Zhao & J A Farrell); Dynamically Connected Fuzzy Single Input Rule Modules and Application to Underactuated Systems (J Yi et al.). Readership: Researchers, graduate and senior level undergraduate students in electrical & electronic engineering, computer engineering, neural networks, fuzzy logic and artificial intelligence.

Computational Intelligence (CI) is a recently emerging area in fundamental and applied research, exploiting a number of advanced information processing technologies that mainly embody neural networks, fuzzy logic and evolutionary computation. With a major concern to exploiting the tolerance for imperfection, uncertainty, and partial truth to achieve tractability, robustness and low solution cost, it becomes evident that composing methods of CI should be working concurrently rather than separately. It is this conviction that research on the synergism of CI paradigms has experienced significant growth in the last decade with some areas nearing maturity while many others remaining unresolved. This book systematically summarizes the latest findings and sheds light on the respective fields that might lead to future breakthroughs.

Written by an expert in the game industry, Christer Ericson's new book is a comprehensive guide to the components of efficient real-time collision detection systems. The book provides the tools and know-how needed to implement industrial-strength collision detection for the highly detailed dynamic environments of applications such as 3D games, virt