71 projects tagged "Artificial Intelligence"
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.
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.
dbacl is a digramic Bayesian text classifier. Given some text, it calculates the posterior probabilities that the input resembles one of any number of previously learned document collections. It can be used to sort incoming email into arbitrary categories such as spam, work, and play, or simply to distinguish an English text from a French text. It fully supports international character sets, and uses sophisticated statistical models based on the Maximum Entropy Principle.
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.
Lush is a Lisp dialect with extensions for object-oriented and array-oriented programming. It is intended as a programming environment for prototyping numerically intensive applications. Unlike alternatives like Python or SciLab, Lush is designed for easy integration of existing C/C++/Fortran codes.
Ciao is a complete Prolog system subsuming ISO-Prolog with a novel modular design which allows both restricting and extending the language. Ciao extensions currently include feature terms (records), higher-order, functions, constraints, objects, persistent predicates, a good base for distributed execution (agents), and concurrency. Libraries also support WWW programming, sockets, and external interfaces (C, Java, TCL/Tk, relational databases, etc.). An Emacs-based environment, a stand-alone compiler, and a toplevel shell are also provided.
Daikon is an implementation of dynamic detection of likely invariants. An invariant is a property (such as "x=2*y+5" or "this.next.prev = this" or "myarray is sorted by <") that holds at a certain point or points in a program. Invariants are often seen in assert statements, documentation, and formal specifications. Invariants can be useful in program understanding and a host of other applications. Daikon runs a program, observes the values that the program computes, and then reports properties that were true over the observed executions. It can detect properties in Java, C, C++, Perl, and IOA programs, in spreadsheet files, and in other data sources.