Projects

Evolving Objects

EO is a template-based, ANSI-C++ evolutionary computation library which helps you to write your own stochastic optimization algorithms insanely fast. With the help of EO, you can easily design evolutionary algorithms that will find solutions to virtually all kind of hard optimization problems ... [More] , from continuous to combinatorial ones. Designing an algorithm with EO consists in choosing what components you want to use for your specific needs, just as building a structure with Lego blocks. [Less]

ulatencyd

μlatencyd is a daemon that optimizes the Linux kernel behavior by using heuristic and cgroups. The daemon uses lua scripts for most heuristic logic.

Wintermute

Wintermute is the attempt of Danté Ashton and a group of others to implement the world's first personal edition of an intelligent framework of applications and libraries, and in the future, an intelligent operating system. This is the brainchild of the [http://www.thesii.org/ SII]. Wintermute ... [More] bolsters the capabilities of using neural networking to learn about its host, a pseudo-langauge engine that permits translations and grammar rulesets of any language to be incorporated into the system, and database downloads of different sets of data to permit the combination of the world's first personal virtual self-thinking assistant. It can be used to perform simple tasks like dictation to a favorite word editor to more complex tasks, like sorting documents depending .. [Less]

Divide and Evolve

A stochastic method for planning decomposition, called Divide-and-Evolve, that was introduced recently and which focuses on plan quality. The basic principle is to search the space of state decompositions of the planning problem at hand by means of artificial evolution: candidate solutions are ... [More] sequences of intermediate goals which define consecutive planning subproblems that are hopefully easier to solve than the global problem. The scope of Divide-and-Evolve is temporal planning as defined by PDDL2.1 (the widely adopted planning domain description language standard) where the problems are described using durative actions and where plan quality is the total makespan. [Less]

a-star-algorithm-implementation

This code is part of the site Justin Heyes-Jones has been running since 2001, teaching folk about the A algorithm. See http://www.heyes-jones.com/astar.html to learn more. The code is designed to be easy to understand, easy to add your own runtime debugging monitoring the open and closed lists ... [More] for example. Efficiency is considered, and the open list is implemented as a priority queue using STL. Now on google hosting, the project is now open to the public to help me maintain different versions and fix bugs. Using a templated class to allow polymorphism without the overhead of vtables. In addition a simplified and fast memory manager is included, speeding up the search. Two canonical examples of A are provided. The 8-puzzle and a path finder. You can email Justin at justinhj@gmail.com Bug reports can also be added to the Issue Tracking section of this site. [Less]

MOEA Framework

The MOEA Framework is an open source Java library for developing and experimenting with multiobjective evolutionary algorithms (MOEAs) and other general-purpose optimization algorithms and metaheuristics. A number of algorithms are provided out-of-the-box, including NSGA-II, ε-MOEA, GDE3 and ... [More] MOEA/D. In addition, third-party tools like JMetal and PISA directly integrate with the MOEA Framework. The MOEA Framework targets an academic audience, providing the resources necessary to rapidly design, develop, execute and statistically test optimization algorithms. This includes over 40 test problems from the literature, and a suite of statistical tools for comparing and analyzing algorithm performance. [Less]

Argorha Pathfinding

Argorha Pathfinding is an algorithm which permit you to find your way into a polygon soup ( 3D world ) efficently by precalculating a system of sectors and portals. It is integrated into GOOF Editor and can be used without that editor. AStar included.

METSlib Optimization Framework

METSlib is an OO (Object Oriented) metaheuristics framework in C++. Model and algorithms are modular: all the implemented search algorithms can be applied to the same model and personalized algorithms can be applied to very different models. METSlib implements the basics of some metaheuristics ... [More] algorithm: Random Restart Local Search, Variable Neighborhood Search, Iterated Local Search, Simulated Annealing (with linear, exponential and custom cooling schedule), and last but not least Tabu Search. [Less]

search-and-find

A implementation of of the following algorithms to solve instances of the Rush-Hour Puzzle: Uniform-cost search, Pure-Heuristic search, A, IDA, Enhanced IDA, RTA These are all implemented using JAVA.

metaheuristicasrepository

Repository for the development of metaheuristic algorithms