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...CUSTOMHyS-Qt is a GUI for the CUSTOMHyS framework, which is an interactive tool for customysing heuristic-based algorithms. The CUSTOMHyS-Qt is written in Python and uses the PyQt5 library for the GUI. Further references about the backend can be found in the CUSTOMHyS repository.
Sudoku Maker is a generator for Sudoku number puzzles. It uses a genetic algorithm internally, so it can serve as an introduction to genetic algorithms. The generated Sudokus are usually very hard to solve -- good for getting rid of a Sudoku addiction.
...GAKNN is built with k- Nearest Neighbour algorithm optimized by the genetic algorithm. Gene annotation datasets saved under .csv or .arff formats with Gene Ontology or FunCat categorization can use GAKNN to predict gene functions.
Deap is a doubly heap for both min and max number access.
A deap is a doubly priority queue for efficient data operations. Both insertion and deletion operations take O(log(N)) time. Access of min or max takes constant time. It can be useful when both min and max are needed in the queue. It can also be used in situations where the number of items is too large and items with low priorities can be dropped with keep memory footprint small.
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EASEA (EAsy Specification of Evolutionary Algorithms: pronounce "easy") is a high-level language dedicated to the specification of evolutionary algorithms. EASEA up to version 0.7 compiles .ez specification files into C++ or JAVA object files.
Flexible job shop scheduling problem (FJSP) is very important in many fields such as production management, resource allocation and combinatorial optimization. In the real manufacturing systems, each operation could be processed on more than one machine and each machine can also process several operations. This feature is known as flexibility.
You can define your problem in this software and get an optimal solution as a Gantt Chart.
This software is based on my M.Sc. thesis of Shahed university (Tehran, Iran).
This project provides a set of Python tools for creating various kinds of neural networks, which can also be powered by genetic algorithms using grammatical evolution. MLP, backpropagation, recurrent, sparse, and skip-layer networks are supported.
Testbed for playing with the algorithm "pagerank" of Google
Provide a testbed to play with pagerank-like algorithm on graph. You can easily add vertices, edges, save the graph for reuse, etc. For now, only Pagerank is implemented, but in the future, other algorithms will be added.
A self-contained, fully configurable Java "game" to simulate multi-species evolution. Design species by optionally specifying every attribute; modify any or all environmental settings; let them loose to eat, fight, procreate, die, and Evolve!
The Mars Rover Simulator project is based on the evolutionary robotics paradigm where an artificial agent acquires its skills through the process of artificial evolution. This simulator can be useful to evolve neural network controllers for the rover
X-GAT (XML-based Genetic Algorithm Toolkit) is a Java framework to optimize problems with Genetic Algorithms (GAs). Differently from other frameworks, X-GAT contains ready-to-use GAs implementations and new features can be easily added.
Sleepwalker aims to provide a highly abstract, universal, reusable, extensible Java-based genetic algorithms framework which can be used as a basis for modelling and programming virtually any practical optimisation problem.
...Evolve them (and control flow) as cycles of arrays in arrays with size constraints based on other array sizes (at specific index) in terms of range, multiply, exponent, or permutation. No working code yet. Whats there now is an extension of GigaLineCompile which would become part of Human AI Net, but there are other projects to finish before I can come back to this one.
This is module for basic computation with floating point numbers. Numbers can have very wide mantissa for good precision, for realize "arbitrary-precision arithmetic". Module was adapt for BCB and MSVC compilers. Russian comments.
The Distributed Genetic Programming Framework is a scalable Java genetic programming environment. It comes with an optional specialization for evolving assembler-syntax algorithms. The evolution can be performed in parallel in any computer network.
A Java implementation of the NEAT algorithm as created by Kenneth O Stanley. Also provides a toolkit for further experiments to be created and can provide both local and distributed learning environments.
MAIF is developed in Java 5 (especially Generics) and aims at building AI algorithms, by concentrating onto the mapping of real-world problems, while abstracting from their inner working. It can be extended with new algorithms and problem representations.