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This project comprises a collection of libraries and applications for the field of program analysis. The starting point is a type analysis for Java programs using Agesen's Cartesian Product Algorithm.
MAGMA: Multiobjective Analyzer for Genetic Marker Acquisition
A genetic algorithm for generating SNP tiling paths from a large SNP database
based on the competing objectives of cost (number of SNPs) and coverage (haplotype blocks):
Hubley R., Zitzler
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Java port and extension of MLC++ 2.0 by Kohavi et al. Currently contains ID3, C4.5, Naive (aka Simple) Bayes, and FSS and CHC (genetic algorithm) wrappers for feature selection. WEKA 3 interfaces are in development.
A collection of implementations of the Lovins stemmer as described in "Development of a Stemming Algorithm" by Julie Beth Lovins (published in "Mechanical translation and computational linguistics", 11:22-31, 1968).
Java Chaotic Random Number Generator - Inspired by chaos theory, the intent of this generator is to produce unseeded, unpredictable numbers. The numbers will not follow a predictable sequence and will not rely on a pseudorandom algorithm.
aVolve is an evolutionary/genetic algorithm designed to evolve single-cell organisms in a micro ecosystem. It currently uses the JGAP Genetic algorithm, but does include a primitive genetic algorithm written in Python.
A java command-line application where the main goal is to solve any simplex problem. It's a team-work school project. It can be usefull for other students who needs to understand the simplex algorithm.
GAZES - Genetic Algorithm Zombie Eradication Simulation Grid-based simulator for zombie scenario. The units will use genetic algorithm to determine their actions on a cycle by cycle basis. This is a school project, so is likely on hiatus for summer.
This project is an implementation of a BML realizer using ROS. The algorithm uses an event-driven architecture, based on Petri nets, to ensure synchronization constraints for robots.
DEAL (Domain Extraction ALgorithm) is an application for domain analysis. Its main purpose is to extract domain information from existing Java applications and to create different kinds of models from the extracted data, including domain-specific languages.
Weka++ is a collection of machine learning and data mining algorithm implementations ported from Weka (http://www.cs.waikato.ac.nz/ml/weka/) from Java to C++, with enhancements for usability as embedded components.