Carlos Cotta

Professor of Computing Languages and Systems, Universidad de Málaga

Bio-inspired algorithms are a broad class of computational procedures inspired by the biological processes and behaviors found in nature, such as biological evolution (as in evolutionary computing), or ant foraging and bird flocking (as in swarm intelligence), designed to solve complex optimization and search problems. As to memetic algorithms (MAs), these are advanced optimization frameworks that orchestrate the synergistic interplay between population-based methods and local-search techniques. While the population-based component is responsible for a broad, global exploration of the search space, the local-search component performs a “fine-tuning” process on individual solutions. Technically speaking, MAs are not necessarily bioinspired, but their most common incarnation is done via the inclusion of local search components within an evolutionary algorithm.

About me

I am a computer scientist working in the field of bioinspired artificial intelligence. I received my MSc degree in Computer Science from the University of Málaga (UMA) in 1995 and went on to earn my PhD from UMA in 1998 with a thesis on hybrid evolutinary algorithms under the supervision of Prof. José María Troya. After completing my doctoral studies, I continued working on this topic, and more generally in the area of memetic computing. I am interested in both theoretical developments and practical applications of these techniques, and particularly in their confluence with complex systems.