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Adaptive Covariance Pattern Search (2021)
Book Chapter
Neri, F. (2021). Adaptive Covariance Pattern Search. In P. A. Castillo, & J. L. Jiménez Laredo (Eds.), Applications of Evolutionary Computation – 24th International Conference, EvoApplications 2021 (178-193). Springer. https://doi.org/10.1007/978-3-030-72699-7_12

Pattern search is a family of single solution deterministic optimisation algorithms for numerical optimisation. Pattern search algorithms generate a new candidate solution by means of an archive of potential moves, named pattern. This pattern is gen... Read More about Adaptive Covariance Pattern Search.

Exploring User Expectations of Brain-Training and Coaching Technologies for Cognitive Health (2020)
Book Chapter
Harrington, K., Craven, M. P., Wilson, M. L., & Landowska, A. (2020). Exploring User Expectations of Brain-Training and Coaching Technologies for Cognitive Health. . Springer Verlag. https://doi.org/10.1007/978-3-030-49065-2_4

User-centred evaluation of brain-training and coaching applications is discussed, with a focus on dementia. A brief outline of outcomes measures used for cognitive training is presented. The design of a set of four patient and public involvement work... Read More about Exploring User Expectations of Brain-Training and Coaching Technologies for Cognitive Health.

Evaluating Automated Machine Learning on Supervised Regression Traffic Forecasting Problems (2020)
Book Chapter
Angarita-Zapata, J. S., Masegosa, A. D., & Triguero, I. (2020). Evaluating Automated Machine Learning on Supervised Regression Traffic Forecasting Problems. In O. Llanes Santiago, C. Cruz Corona, A. J. Silva Neto, & J. L. Verdegay (Eds.), Computational intelligence in emerging technologies for engineering applications (187-204). Springer. https://doi.org/10.1007/978-3-030-34409-2_11

© Springer Nature Switzerland AG 2020. Traffic forecasting is a well-known strategy that supports road users and decision-makers to plan their movements on the roads and to improve the management of traffic, respectively. Current data availability an... Read More about Evaluating Automated Machine Learning on Supervised Regression Traffic Forecasting Problems.

Migration threshold tuning in the deterministic dendritic cell algorithm (2019)
Book Chapter
Greensmith, J. (2019). Migration threshold tuning in the deterministic dendritic cell algorithm. In C. Martín-Vide, G. Pond, & M. A. Vega-Rodríguez (Eds.), Theory and Practice of Natural Computing: 8th International Conference, TPNC 2019, Kingston, ON, Canada, December 9–11, 2019: proceedings (122-133). Springer. https://doi.org/10.1007/978-3-030-34500-6_8

In this paper we explore the sensitivity of the migration threshold parameter in the Deterministic Dendritic Cell Algorithm (dDCA), one of the four main types of Artificial Immune System. This is with a view to the future construction of a DCA augmen... Read More about Migration threshold tuning in the deterministic dendritic cell algorithm.

Discomfort—the dark side of fun (2018)
Book Chapter
Benford, S., Greenhalgh, C., Giannachi, G., Walker, B., Marshall, J., Tennent, P., & Rodden, T. (2018). Discomfort—the dark side of fun. In M. Blythe, & A. Monk (Eds.), Funology 2: from usability to enjoyment (209-224). Springer. https://doi.org/10.1007/978-3-319-68213-6_13

For many of us, the notion of ‘fun’ conjures up visions of experiences that are amusing, pleasant, entertaining, playful—perhaps even frivolous. Rides, games, shows and perhaps even the experience of visiting an art gallery can embody these senses of... Read More about Discomfort—the dark side of fun.