The main goal of the Cognitive Vision project is to improve the results of artificial intelligence. The current scope is to equip the abilities of the AIBO (robot dog of the Sony) to explore its environment and to recognize the local position (e.g. navigation in a room). The first trial is to use and develop image processing methods with a single webcam and to apply these techniques with AIBO.
tinyMAS is a multiagent platform that provides base concepts (such as kernel, message, yellow pages, white pages, and transport service) and extended concepts (such as environment, influence, and perception). It aims to provide an easy-to-understand and and easy-to-use platform dedicated for multiagent engineer/research courses. TinyMAS is no longer under development. A large amount of its source code has been merged into the Janus platform.
METSlib is an object-oriented metaheuristics framework in C++ designed to make implementing or adapting models easy. The model is modular: all the implemented search algorithms can be applied to the same model. METSlib implements the basics of some metaheuristics algorithms, such as Random Restart Local Search, Variable Neighborhood Search, Iterated Local Search, Simulated Annealing, and Tabu Search. For each algorithm, you must implement an objective function, a neighborhood (move manager), and some moves. Tabu Search is one of the fastest ways to generate near-optimal solutions to a wide range of hard combinatorial optimization problems.
Aseba is an event-based architecture for distributed control of mobile robots. It targets integrated multi-processor robots or groups of single-processor units, real or simulated. The core of aseba is a lightweight virtual machine tiny enough to run even on microcontrollers. Robots are programmed in a user-friendly scripting language using a cozy integrated development environment.
Jigsaw is an embedded data-store designed for the development of data-warehouse, analytical, and machine learning applications. Jigsaw can perform over one million operations a second, and scale to store tera-bytes of data. The object library contains classes for representing ordered and unordered mappings, highly compressed bit vectors with a range of set theoretic operators, and directly integrates a high performance sort system.
libagf is a fast, innovative implementation of adaptive or variable-bandwidth kernel-based estimators for statistical classification, PDF estimation, and interpolation/non-linear regression. It is written in C++ and includes simple, command line executables as well as easy-to-use libraries.
Nomatic*IM provides a service that supports the convenient and appropriate broadcasting of presence through instant messaging clients. It provides the flexibility to support multiple IM protocols, IM clients, and operating systems. From a high-level, what Nomatic*IM does is to figure out where you are and what you are doing from the sensors that come with your computing platform. That information is processed with machine learning techniques to develop a semantic interpretation about the name of your current place, activity, and social context.
Logic Reasoner is a theorem prover for first-order logic with equality. The main objective leading the development of Logic Reasoner has been the creation of a flexible architecture: in particular, the program has been designed as a generic infrastructure for theorem proving, which forms the basis for a collection of specific proving techniques. These techniques can be easily combined or replaced to create configurations with different properties.