5 papers · 1 filter
The Paradox of Success in Evolutionary and Bioinspired Optimization: Revisiting Critical Issues, Key Studies, and Methodological Pathways
Daniel Molina, Javier Del Ser, Javier Poyatos +1
Evolutionary and bioinspired computation are crucial for efficiently addressing complex optimization problems across diverse application domains. By mimicking processes observed in…
A Tutorial on the Design, Experimentation and Application of Metaheuristic Algorithms to Real-World Optimization Problems
Eneko Osaba, Esther Villar-Rodriguez, Javier Del Ser +6
In the last few years, the formulation of real-world optimization problems and their efficient solution via metaheuristic algorithms has been a catalyst for a myriad of research st…
A Prescription of Methodological Guidelines for Comparing Bio-inspired Optimization Algorithms
Antonio LaTorre, Daniel Molina, Eneko Osaba +2
Bio-inspired optimization (including Evolutionary Computation and Swarm Intelligence) is a growing research topic with many competitive bio-inspired algorithms being proposed every…
Emerging NeoHebbian Dynamics in Forward-Forward Learning: Implications for Neuromorphic Computing
Erik B. Terres-Escudero, Javier Del Ser, Pablo GarcÃa-Bringas
Advances in neural computation have predominantly relied on the gradient backpropagation algorithm (BP). However, the recent shift towards non-stationary data modeling has highligh…
Evolutionary Computation for the Design and Enrichment of General-Purpose Artificial Intelligence Systems: Survey and Prospects
Javier Poyatos, Javier Del Ser, Salvador Garcia +6
In Artificial Intelligence, there is an increasing demand for adaptive models capable of dealing with a diverse spectrum of learning tasks, surpassing the limitations of systems de…