The Self-Evolving Agent Ecosystem — Trading agents that evolve through Darwinian selection and adversarial self-play
Generating Evolutionary Opponents as a Reinforcement Guided Exploration Solution
GrafoRVFL: A Gradient-Free Optimization Framework for Boosting Random Vector Functional Link Network
Transfer learning on head pose estimation problem enhanced by neural architecture search.
A comprehensive collection of evolutionary AI projects built with NEAT algorithm showcasing intelligent behavior development in Car, Snake, and Pong games.
Asteroids game with AI agents trained over generations using neural networks and a genetic algorithm. Built with Pygame.
A high-performance Python implementation of Dawkin's Weasel experiment. Uses multiprocessing and matplotlib to visualise how different mutation rates affect evolutionary convergence speed.
Solving N-Queens problem by Simple Genetic Algorithm in Python.
Python tool that uses seeded and non-seeded genetic algorithms to generate date-validation test cases, measure category coverage, and export evolved test suites to CSV.
A high-performance optimization engine designed to solve complex combinatorial problems. This solver implements custom selection, crossover, and mutation strategies to evolve optimal solutions for tasks like scheduling, resource allocation, and pathfinding.
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