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.
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.
PEDSIM is a microscopic pedestrian crowd simulation system. The PEDSIM library allows you to use pedestrian dynamics in your own software. Based on pure C++/STL without additional packages, it runs on virtually every operating system. The PEDSIM Demo Application (Qt) gives you a quick overview of the capabilities, and is a starting point for your own experiments. PEDSIM is suitable for use in crowd simulations (e.g. indoor evacuation simulation, large scale outdoor simulations), where one is interested in output like pedestrian density or evacuation time. The quality of the individual agent's trajectory is high, PEDSIM can be used for creating massive pedestrian crowds in movies. Since libpedsim is easy to use and extend, it is a good starting point for science projects.
The Graphical Models Toolkit (GMTK) is a toolkit for rapidly prototyping statistical models using dynamic graphical models (DGMs) and dynamic Bayesian networks (DBNs). It can be used for speech and language processing, bioinformatics, activity recognition, and any time series application. It features exact and approximate inference, many built-in factors including dense, sparse, and deterministic conditional probability tables, native support for ARPA backoff-based factors and factored language models, parameter sharing, gamma and beta distributions, dense and sparse Gaussian factors, heterogeneous mixtures, deep neural network factors, and time-inhomogeneous trellis factors, arbitrary order embedded Markov chains, a GUI graph viewer, and much more.
fuzzylite is a fuzzy logic control library. Its goal is to allow you to easily create fuzzy logic controllers in a few steps utilizing object-oriented programming without requiring any third-party libraries. qtfuzzylite is a Qt-based GUI for fuzzylite. Its goal is to allow you to visually design your fuzzylite controllers and interact with them in real time.