Papers
4
Total Citations
33
H-Index
2
About
Iñaki Fernández Pérez is a researcher in swarm robotics and evolutionary computation, with a focus on distributed embodied evolution—a field where robot collectives autonomously adapt their behaviors through on-board, online evolutionary algorithms. His major contributions center on understanding how selection methods and diversity maintenance shape the learning capabilities of robot swarms. In his most cited work, "Learning collaborative foraging in a swarm of robots using embodied evolution" (2017, 15 citations), he demonstrated how swarms can collectively evolve cooperative foraging strategies without central control. His 2014 study comparing selection methods in on-line distributed evolutionary robotics (14 citations) proposed a novel variant of the mEDEA algorithm that incorporates selection operators, systematically evaluating four approaches to drive task-oriented adaptation. Further, his 2018 work on maintaining diversity in robot swarms addressed a critical challenge in embodied evolution—preventing premature convergence. Fernández Pérez’s research bridges theoretical evolutionary algorithms and practical multi-robot systems, offering insights into how decentralized, adaptive swarms can solve complex tasks. His work is particularly valuable for students and researchers interested in autonomous robotics, collective intelligence, and the engineering of resilient, self-organizing systems.
Research Focus
Key Achievements
Top Papers
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- 2Comparison of Selection Methods in On-Line Distributed Evolutionary Robotics14 citations · 2014
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