Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics ; International Workshop, SLS 2007, Brussels, Belgium, September 6-8, 2007, Proceedings
Stochastic local search (SLS) algorithms enjoy great popularity as powerful and versatile tools for tackling computationally hard decision and optimization pr- lems from many areas of computer science, operations research, and engineering. However, in recent years it has become evident that at the core of this development task there is a highly complex engineering process, which combines various aspects of algorithm design with empirical analysis techniques and problem-specific background, and which relies heavily on knowledge from a number of disciplines and areas, including computer science, operations research, artificial intelligence, and statistics. This development process needs to be - sisted by a sound methodology that addresses the issues arising in the various phases of algorithm design, implementation, tuning, and experimental eval- tion.
Computers and Games ; 5th International Conference, CG 2006, Turin, Italy, May 29-31, 2006, Revised Papers
This book covers all aspects of artificial intelligence in computer-game playing. Topics addressed are evaluation and learning, search, combinatorial games and theory opening and endgame databases, single-agent search and planning, and computer Go.
Applied Parallel Computing ; State of the Art in Scientific Computing ; 8th International Workshop, PARA 2006, Umea, Sweden, June 18-21, 2006, Revised Selected Papers
It covers partial differential equations, parallel scientific computing algorithms, linear algebra, simulation environments, algorithms and applications for blue gene/L, scientific computing tools and applications, parallel search algorithms, peer-to-peer computing, mobility and security, algorithms for single-chip multiprocessors.
A Modular Calculus for the Average Cost of Data Structuring
This volume, with forewords by Greg Bollella and Dana Scott, presents novel programs based on the new advances in this area, including the first randomness-preserving version of Heapsort. Programs are provided, along with derivations of their average-case time, to illustrate the radically different approach to average-case timing. The automated static timing tool applies the Modular Calculus to extract the average-case running time of programs directly from their MOQA code.



