Programmatic modification and evaluation of software
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Updated
Sep 19, 2024 - Common Lisp
Programmatic modification and evaluation of software
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Implementation of metaheuristic optimization methods in Python for scientific, industrial, and educational scenarios. Experiments can be executed in parallel or in a distributed fashion. Experimental results can be evaluated in various ways, including diagrams, tables, and export to Excel.
Evolutionary Algorithms implementations, for various (discrete & continuous) optimization problems, including for autonomous agent control.
🐒 Plan, develop and simulate evolving programs.
A python library for optimization, geared towards modular robots and evolutionary computing.
A (still growing) paper list of Evolutionary Computation (EC) published in some (rather all) top-tier (and also EC-focused) journals and conferences. For EC-focused publications, only Parallel/Distributed EC are covered in the current version.
A Java library of Customizable, Hybridizable, Iterative, Parallel, Stochastic, and Self-Adaptive Local Search Algorithms
Este repositorio contiene el código desarrollado para mi Trabajo de Fin de Grado en Ingeniería Informática.
Genetic Programming (GP) library for C++. Type-safe replacement for lilgp, et al. Integreates directly into the C++ typesystem.
PhD Candidate in Artificial Intelligence. Applying machine learning to fish oil analysis.
This course covers the applied side of algorithmics in machine learning and deep learning, focusing on hands-on coding experience in Python.
A game that is developed as an assignment for Computer Intelligence course.
Distributed GPU-Accelerated Framework for Evolutionary Computation. Comprehensive Library of Evolutionary Algorithms & Benchmark Problems.
An evolutionary algorithm library in Java
Transforming Neural Architecture Search (NAS) into multi-objective optimization problems. A benchmark suite for testing evolutionary algorithms in deep learning.
OptiRouteX is a program designed to optimize and calculate the shortest possible route between specified locations using genetic algorithms.
Data Analysis with R
Exploring the application of a Genetic Algorithm to evolve harmonographs
Implement an evolutionary solution for the 8-queens problem and apply a genetic algorithm with specific properties.
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