SPatial Analysis With self-organizing Neural Networks
The SPAWNN toolkit is an innovative toolkit for spatial analysis with self-organizing neural networks which is particularily useful for spatial analysis, visualization and geographical data mining. To run the toolkit, simply download and execute (double-click) the jar-file. Please cite: - Hagenauer, J., & Helbich, M. (2016). SPAWNN: A Toolkit for SPatial Analysis With Self-Organizing Neural Networks. Transactions in GIS, 20(5), 755-775. Other related publications: - Hagenauer, J. (2016). Weighted merge context for clustering and quantizing spatial data with self-organizing neural networks. Journal of Geographical Systems, 18(1), 1-15. - Hagenauer, J., & Helbich, M. (2013). Contextual neural gas for spatial clustering and analysis. International Journal of Geographical Information Science, 27(2), 251-266.
SmartSoft is a framework for developing component-based robotics systems. SmartSoft components are based on a small set of predefined component interaction patterns to strictly enforce component decoupling and to support off-the-shelf reuse.
Your language to speak with all.
This project has the language data for spel, the main new codebase is at: https://gitlab.com/liberit/pyac A computer programming language using human language syntax for human-to-human and human-to-computer communication with high precision, supporting many languages. Currently has alpha prototype support for analytic versions of the UN languages English, Mandarin Chinese, Spanish, Arabic, Russian and French as well as a bunch of others in addition to the core mwak language. The alpha IDE is at http://spel.sourceforge.net/src/web/spel.html (wait for it to finish loading before clicking "translate") Since it is early prototype, it's not easy to use, If you are interested, join the mailing list. latest code is in the git repository.
Sunsetter, a chess, crazyhouse, and bughouse playing program
A Bughouse/w24 and Crazyhouse/w23 playing program. C++ , Linux/Windows, GPL. Also available in precompiled packages to start playing right away.
The Teachingbox uses advanced machine learning techniques to relieve developers from the programming of hand-crafted sophisticated behaviors of autonomous agents (such as robots, game players etc...) In the current status we have implemented a well founded reinforcement learning core in Java with many popular usecases, environments, policies and learners. Obtaining the teachingbox: FOR USERS: If you want to download the latest releases, please visit: http://search.maven.org/#search|ga|1|teachingbox FOR DEVELOPERS: 1) If you use Apache Maven, just add the following dependency to your pom.xml: <dependency> <groupId>org.sf.teachingbox</groupId> <artifactId>teachingbox-core</artifactId> <version>1.2.0</version> </dependency> 2) If you want to check out the most recent source-code: svn checkout https://svn.code.sf.net/p/teachingbox/code/trunk teachingbox-trunk or browse files: https://sourceforge.net/p/teachingbox/code/HEAD/tree/trunk/
Experience AI ( Computer Plays with You ) !
SmartPrediction-ENGINE inside Enhanced with Artificial Intelligence Based upon Game Theory Still This is in BETA Phase
C++ header only library with AI and bioinformatics algorithms
C++ header only library, small and fast; Naive Bayesian Classifier, Decision Tree Classifier (ID3), DNA/RNA nucleotide second structure predictor, timeseries management, timeseries prediction, generic Evolutionary Algorithm, generic Hill Climbing algorithm and others.
Fast C++ KNN classifier
KNN Classifier library for C++, at background using armadillo. In k-NN classification, the output is a class membership. An object is classified by a majority vote of its neighbors, with the object being assigned to the class most common among its k nearest neighbors (k is a positive integer, typically small). If k = 1, then the object is simply assigned to the class of that single nearest neighbor.
This is an implementation of a machine learning library in C++11
Nunn implements an artificial intelligent framework written in modern C++11, which supports artificial networks able to learn by example and other machine learning algorithms. The project includes demo applications, which are an excellent prototype problem for neural networks learning: - mnist_test application lets you evaluate multiple net configurations on MNIST - ocr_test provides a GUI to write digits that can recognize by using MNIST trained nets - TicTacToe game - Xor-function implementation - And-perceptron sample - Hopfield test Binaries for Windows have been built by using Microsoft Visual C++ 2015, so you may need to install Visual C++ Redistributable Packages. To do this, search for "Visual C++ Redistributable Packages for Visual Studio 2015" or use the link https://www.microsoft.com/en-us/download/details.aspx?id=48145
a UCI chess engine
OliveChess is a simple chess engine compatible with modern chess interfaces such as ChessBase products, Arena and XBoard/Winboard. The engine supports UCI and XBoard protocols. Note: in order to use it as an xboard engine you may need Polyglot tool to be installed first
Part-of-speech tagging is the task of assigning symbols from a particular set to words in a natural language text. ACOPOST implements and extends well-known machine learning techniques and provides a uniform environment for testing.
Since version 1.4 (inclusive) the project was moved to https://github.com/bagaturchess/Bagatur-Chess-Engine-And-Tools Bagatur chess engine and tools. Keywords: Reusable Bit Board, PGN tool, TPT implementation with LRU discipline and hashkeys, MTD parallel search based on PV alpha-beta, adaptive move ordering
This project aims to develop and share fast frequent subgraph mining and graph learning algorithms. Currently we release the frequent subgraph mining package FFSM and later we will include new functions for graph regression and classification package
A framework for the development of intelligent systems.
QSMM, a recursive acronym for "QSMM State Machine Model", is a framework for learning finite automatons that perform goal-directed interaction with entities which exhibit deterministic or stochastic behavior. The learning process can be carried out in real time together with the interaction process. A basic building block for supporting state models of finite automatons is adaptive probabilistic mapping, which for an argument from its domain returns more often results that maximize or minimize values of one or more objective functions. Finite automatons can be represented by assembler programs with user-defined instructions that perform effective work. To assist in the learning of a finite automaton, a template for its state model can be provided as an assembler program with probabilistic jump instructions. The operating principle behind the framework resembles the Boltzmann machine.
A Vietnamese dependency parsing toolkit
VnDP is a Vietnamese dependency parsing toolkit which integrates a pre-trained parsing model and a pre-trained POS tagging model. The parsing model was trained on our VnDT Vietnamese dependency Treebank which was automatically converted from the Vietnamese constituent Treebank. See more details in VnDP's website at http://vndp.sourceforge.net/
AFNER is a C++ named entity recognition system that uses machine learning techniques. It is customisable to various domains. It also allows for multiple and overlapping named entity labels.
Java Framework for Artificial Intelligence Search Agents algorithms
Freeware experimental artificial intellectual systems based on self-organization of chaotic digital network. The peculiarity of this system is that the digital network created using radionic* technology that provides interaction between human and computer thinking. This digital network of the brain obtained by the interaction of the operator with the software, on the basis of generating random sequences at pomotsi quark-neuronal cluster. Thus, in part, this artificial neural network is a replica of the brain.
Local-search based solver of Constraint Satisfaction and Optimization Problems.
A lightweight IDE for Artificial Intelligence. Started as GUI for the Euler reasoning engine. The sources can be N3, RDF, OWL, UML, eCore, plain XML or XSD, files or URL's. Wraps Drools (or CWM, FuXi) as N3 rules engines. Model based app. generation.
Gamera is a framework for the creation of structured document analysis applications by domain experts. It combines a programming library with GUI tools for the training and interactive development of recognition systems.
This project consists of various implementations of the Graphplan algorithm. At the moment we have two implementations of Graphplan: * Emplan - A C++ implementation for Linux, Windows and MacOS X * JavaGP - A Java implementation
Declarative knowledge representation and reasoning
This is the old release page of the IDP system, please visit http://dtai.cs.kuleuven.be/software/idp/try for the most recent release.
Jamocha is an open source rule engine. The objective of Jamocha is to provide a high quality rule engine and expert system shell environment. We would provide you an engine, the required development tools and a best practice methodology.