SHOGUN is a machine learning toolbox whose focus is on large scale kernel methods and especially on Support Vector Machines (SVM). It provides a generic SVM object interfacing to several different SVM implementations, all making use of the same underlying, efficient kernel implementations. Apart from SVMs and regression, SHOGUN also features a number of linear methods like Linear Discriminant Analysis (LDA), Linear Programming Machine (LPM), (Kernel) Perceptrons, and algorithms to train hidden Markov models. SHOGUN can be used from within C++, Matlab, R, Octave, and Python.
Fuzzy machine learning framework is a library and a GUI front-end for machine learning using intuitionistic fuzzy data. The approach is based on the intuitionistic fuzzy sets and the possibility theory. Further characteristics are fuzzy features and classes; numeric, enumeration features and features based on linguistic variables; user-defined features; derived and evaluated features; classifiers as features for building hierarchical systems; automatic refinement in case of dependent features; incremental learning; fuzzy control language support; object-oriented software design with extensible objects and automatic garbage collection; generic data base support through ODBC; text I/O and HTML output; an advanced graphical user interface based on GTK+; and examples of use.
The Noble Ape Simulation is a collection of a number of autonomous simulation components including a landscape simulation, biological simulation, weather simulation, sentient creature (Noble Ape) simulation, and a simple intelligent-agent scripting language (ApeScript). Noble Ape also contains a social simulation where the Noble Apes can be tracked in terms of social groups and also over many generations to explain social phenomenon to users looking to study this kind of interaction. It has been in development for more than a fifteen years.
QSMM, the "QSMM State Machine Model", is a framework for development of non-deterministic intelligent state models and systems with spur-driven behavior. It includes low-level functions for generating optimal actions by the system and high-level functions for building multinode models. In a multinode model, nodes represent components of a system you develop which choose optimal actions using the framework and can correspond to entities external to the system and which behavior is to be learnt. A node can choose optimal actions based on a current node state which is either set manually by your program or is identified automatically by the framework. Probability profiles for a state transition matrix and an action emission matrix of the node can be specified using an assembler program with a user-defined instruction set.
SIP provides image processing, pattern recognition, and computer vision routines for SciLab, a Matlab-like matrix-oriented programming environment. SIP is able to read/write images in almost 90 major formats, including JPEG, PNG, BMP, GIF, FITS, and TIFF. It includes routines for filtering, segmentation, edge detection, morphology, curvature, fractal dimension, distance transforms, multiscale skeletons, and more.
Conquest is a simultaneous turn-based strategy game placed in a dark and distant future. Play the role of a futuristic commander. Divide your armies and conquer the world. Position satellites to reveal your opponents. Launch missiles to annihilate big armies, but watch out for incoming drop pods behind your back. Standing in your path to victory are other commanders like yourself. Fight them off one by one and prove you are the greatest of the great. The combination of fast gameplay and randomly generated maps equals intense, restless nights of battles for cities. Drag and drop your way to victory.
Into is a cross-platform machine intelligence application framework written in C++. Into provides a different, fast way to build high-performance applications for image analysis, machine vision, pattern recognition, and artificial intelligence. It features a layered API and more than 20 fully interoperable plug-in modules for accessing image and data sources, powerful feature extractors, classifiers, neural networks, and much more. It also provides Ydin, an innovative execution engine that makes it easy to create dynamic programs that automatically run in parallel, enabling you to create more with less hassle, less code, and less time. Into uses Qt to let you create beautiful user interfaces for your applications with ease.
Urbi is a robotics software platform. It includes a C++/Java middleware API called UObject to interface components such as motors, cameras, and algorithms, and an innovative scripting language, urbiscript, with built-in support for parallel and event-based programming, used to write high-level behaviors and orchestrate the interactions between components. UObject components are built as shared libraries exposed as native objects within urbiscript, and either hot-plugged in a running Urbi engine, or started as a remote autonomous process communicating with the engine via the network. At any time, new urbiscript code can be sent to a running Urbi engine via a simple telnet, to introspect the state of components, modify existing code, or add new behaviors. Urbi is cross-platform and supports several robots (Gostai Jazz, Lego Mindstorms, Aldebaran Nao, Segway RMP, Spykee, Bioloid, etc.) and a simulator (Webots).
Fast Artificial Neural Network Library is a neural network library that implements multilayer artificial neural networks in C with support for both fully connected and sparsely connected networks. Cross-platform execution in both fixed and floating point are supported. It includes a framework for easy handling of training data sets. It is easy to use, versatile, well documented, and fast. C++, Perl, PHP, .NET, Python, Delphi, Octave, Pure Data, and Mathematica bindings are available. A reference manual accompanies the library with examples and recommendations on how to use the library. A graphical user interface is also available for the library.