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.
fuzzylite is a cross-platform fuzzy logic control library. It provides a natural and simple way of creating a fuzzy logic engine in a few steps using object-oriented programming. It allows you to easily add your own features to the library by just using inheritance. It only relies on the Standard Template Library (STL) which comes with C++. No third-party libraries (e.g., boost) are involved. As a library, it only contains the functions you need from a fuzzy logic controller. qtfuzzylite is a Graphic User Interface which uses fuzzylite to provide a nice and easy way to visually create your fuzzy logic controllers. It allows you to design your fuzzy logic controller and interactively play with it while observing its operation in realtime, and it allows you to export your controller to actual fuzzylite C++ code, so you only need to copy and paste it into your C++ application.
Thinknowlogy is grammar-based software designed to utilize the logic contained within grammar in order to create intelligence through a natural language, which is demonstrated by programming in a natural language, reasoning in a natural language (drawing conclusions, making assumptions (with a self-adjusting level of uncertainty), asking questions (about gaps in the knowledge), and detecting conflicts), and intelligent answering of "is" questions, providing alternative answers as well.
Wandora is a general purpose data extraction, management, and publishing application based on Topic Maps and Java. Wandora has a graphical user interface, layered presentation of knowledge, several data storage options, rich data extraction, import and export capabilities, and an embedded HTTP server that enables dynamic publication of Topic Maps. Wandora is well suited for rapid ontology construction and knowledge mashups.
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.