Bio4Res

New Bioinspired Techniques for Resilience and Sustainability (2022-26)

We study the factors and methods whereby bioinspired techniques can be endowed with resilience to different kind of disturbances, as well as the conditions under which these methods can be run in a sustainable way. We also consider the application of bioinspired algorithms to domains in which resilience is sought.

DeepBio

New Bioinspired Computing Models for Massively Complex Environments (2018-2021)

This project revolves around the idea of massively complex environments, and the deployment of bioinspired algorithms onto them. Complexity is here a feature of the underlying computational substrate on which the bioinspired algorithms are executed, and the problem/data environment the algorithm is tackling.

EphemeCH

Bioinspired Algorithms in Complex Ephemeral Environments (2015-17)

This project examines the broad area where bioinspired algorithms, distributed systems, ephemeral computing systems, self-star properties and complex systems interact. We focus on the use of bioinspired algorithms to analyze, model and optimize ephemeral computation environments, and the deployment of bioinspired systems on ephemeral computing environments to solve complex problems

AnySELF

Self-* Properties in Memetic Algorithms for Complex Optimization Problems (2012-14)

The project deals with self-adaptive, self-healing, self-monitoring properties in complex systems, and tries to leverage evolutionary algorithms for generating those features mainly in distributed computing systems.

NEMESIS

New Metaheuristics for Finding Subjectively Interesting Solutions (2009-11)

The project focuses on the use of bioinspired metaheuristics for perfoming user-centric optimization.