Resilient Bioinspired Algorithms: A Computer System Design Perspective - Cotta-Porras, Carlos; Oague, Gustavo (SpringerLink, 2022)
Resilience can be defined as a system's capability for returning to normal operation after having suffered a disruption. This notion is of the foremost interest in many areas, in particular engineering. We argue in this position paper that is is a crucial property for bioinspired optimization algorithms as well. Following a computer system perspective, we correlate some of the defining requirements for attaining resilient systems to issues, features, and mechanisms of these techniques. It is shown that bioinspired algorithms do not only exhibit a notorious built-in resilience, but that their plasticity also allows accommodating components that may boost it in different ways. We also provide some relevant research directions in this area.
This preprint has not undergone peer review or any post-submission improvements or corrections. The Version of Record of this contribution is published in Cotta, C., Olague, G. (2022). Resilient Bioinspired Algorithms: A Computer System Design Perspective. In: Jiménez Laredo, J.L., Hidalgo, J.I., Babaagba, K.O. (eds) Applications of Evolutionary Computation. EvoApplications 2022. Lecture Notes in Computer Science, vol 13224. Springer, Cham. https://doi.org/10.1007/978-3-031-02462-7_39
Keywords: Sistemas informáticos; Algoritmos; Resilience; Bioinspired Optimization; Robustness; Computer Systems