A lightweight, generic C++11 framework for evolutionary computation
Robot evolution framework for the Triangle of Life project
Evolutionary Computation: A Modern Perspective |<...>| This is an online book, which is free-access and actively-updated (1st Edition: from 2023 to 2027).
Roborobo v.4 - super fast multi-robot simulator for evolutionary swarm robotics and multi-agent learning. Combines ease-of-use (python interface) with speed (C++ core engine).
A modified benchmark for designing and controlling 2D Voxel-based Soft Robots
Repository replicating the design- and behaviour-adaptation algorithm using reinforcement learning algorithm presented in the paper " Data-efficient Co-Adaptation of Morphology and Behaviour with Deep Reinforcement Learning"
A topology and parameter evolving universal learning network.
Code for "Evolution and learning in differentiable robots", Strgar et al., Proceedings of Robotics: Science and Systems (RSS) 2024
This is the official repository for the ALIFE paper "Shape Change and Control of Pressure-based Soft Agents" and its Artificial Life journal extension "Pressure-based Soft Agents".
This is the official repository for the GECCO (Genetic and Evolutionary Computation Conference, 2022) paper "A Comparative Analysis on Genome Pleiotropy for Evolved Soft Robots". This repository hosts all the code necessary to replicate the experiments. This work was carried out at Ghent University IDLab-AIRO.
This is the official repository for the GECCO paper "Morphology Choice Affects the Evolution of Affordance Detection in Robots".
This repository hosts the code used in the paper "Collective control of modular soft robots via embodied Spiking Neural Cellular Automata"
This repository hosts the code used in the paper "An Experimental Comparison of Evolved Neural Network Models for Controlling Simulated Modular Soft Robots".
This study uses evolutionary collective robotics as an experimental platform to investigate the impact of increasing task environment complexity (collective behavior task difficulty) on the evolution and benefits of morphological and behavioral diversity in robotic swarms.
This work was carried out at Ghent University (IDLab-AIRO), in collaboration with the Vrije Universiteit Brussel (R&MM).
Repository containing results and the algorithms described in the article: https://periodicos.ufsm.br/coming/article/view/85256
Python API with evolutionary computation and reinforcement learning algorithms for Khepera simulation engine
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