The ATRACO Project is a prototype implementation of a trusted ambient ecology system that runs and manages activity spheres in an Ambient Intelligence Space. Activity spheres are realized by automatically discovering, selecting, and adapting smart devices (artefacts) existing in the space, according to user's preferences, customs, and activities. OWL ontologies are used for modeling user profile, devices, activities, and goal descriptions. Abstract plans are bound to specific devices, methods, and values through semantic matching.
EO is a template-based, ANSI-C++ evolutionary computation library that helps you to write your own stochastic optimization algorithms quickly. Evolutionary algorithms form a family of algorithms inspired by the theory of evolution, and solve various problems. They evolve a set of solutions to a given problem in order to produce the best results. These are stochastic algorithms because they iteratively use random processes. The vast majority of these methods are used to solve optimization problems, and may be also called "metaheuristics". They are also ranked among computational intelligence methods, a domain close to artificial intelligence. With the help of EO, you can easily design evolutionary algorithms that will find solutions to virtually all kind of hard optimization problems, from continuous to combinatorial ones.