Weka is a collection of machine learning algorithms for solving real-world data mining problems. It is written in Java and runs on almost any platform. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka is also well-suited for developing new machine learning schemes. The development version contains a GUI with visualization tools and direct database access.
EAsea Specification of Evolutionary Algorithms (EASEA), is a high-level language dedicated to the specification of evolutionary algorithms. The language and compiler are quite mature. EASEA compiles .ez specification files into C++ or Java object files, using existing evolutionary libraries. Supported C++ libraries currently are GALib or EO.
YAKS - Yet Another Khepera Simulator, is a Khepera simulator that uses prerecorded sensor values from a real robot in order to provide simulation speeds of 3600 times reality. It has support for the infrared sensors, light sensors, K213 vision turret, gripper arm, and more. The simulator comes with a GTK interface, a genetic algorithm (GA), and an artificial neural net (ANN).
myBeasties is a highly flexible evolutionary programming module. It is designed to be extendable and customisable for maximum use by the Perl developer. Many species of genotypes can be evolved, and these can be used to build phenotypes of any size or complexity. These can be as simple as a list or as large as a whole class of objects.
The RoboCup Soccer Simulator is a platform for evaluating multiple autonomous intelligent agents in a realworld-like domain. The simulator allows two teams of 11 players and one coach to interact in a simulated game of soccer. The team members connect to the simulator using UDP sockets and must perform complex behaviors using only a few basic commands, primarily dash, kick, turn, and catch, based on noisy and infrequent sensor information provided by the simulator. This simulator is used in the simulation league of the RoboCup competition.
Allegro Common Lisp is a full ANSI Common Lisp (1994) implementation. It contains many extensions, including 32- and 64-bit native compilation, efficient built-in memory management, foreign functions (for interfacing with other languages), multiprocessing, UNICODE and locale support, XML/HTML parsers, a Web client and server, GTK+ interface (1.2 and 2.0), Java interface, OLE interface (Windows only), profiler, regular expressions, an XML RPC implementation, native Lisp RPC, sockets, DLL and shared library support, and more.
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.
Turing Machine (C++ Implementation) is a Turing machine simulation that is defined by a series of input files. These include a metafile containing data related to some Turing machine, a states file containing a list of initial, halting, and internal states, an alphabet file of empty, input, and internal symbols, a transition file of transition rules, and input word files, which detail the input given on a tape.