All Outputs (7)

Learning Descriptors for Novelty-Search Based Instance Generation via Meta-evolution (2024)
Conference Proceeding
Marrero, A., Segredo, E., León, C., & Hart, E. (in press). Learning Descriptors for Novelty-Search Based Instance Generation via Meta-evolution. In Genetic and Evolutionary Computation Conference (GECCO ’24), July 14–18, 2024, Melbourne, VIC, Australia. https://doi.org/10.1145/3638529.3654028

The ability to generate example instances from a domain is important in order to benchmark algorithms and to generate data that covers an instance-space in order to train machine-learning models for algorithm selection. Quality-Diversity (QD) algorit... Read More about Learning Descriptors for Novelty-Search Based Instance Generation via Meta-evolution.

Generating diverse and discriminatory knapsack instances by searching for novelty in variable dimensions of feature-space (2023)
Conference Proceeding
Marrero, A., Segredo, E., Hart, E., Bossek, J., & Neumann, A. (2023). Generating diverse and discriminatory knapsack instances by searching for novelty in variable dimensions of feature-space. In GECCO '23: Proceedings of the Genetic and Evolutionary Computation Conference (312-320). https://doi.org/10.1145/3583131.3590504

Generating new instances via evolutionary methods is commonly used to create new benchmarking data-sets, with a focus on attempting to cover an instance-space as completely as possible. Recent approaches have exploited Quality-Diversity methods to ev... Read More about Generating diverse and discriminatory knapsack instances by searching for novelty in variable dimensions of feature-space.

A Novelty-Search Approach to Filling an Instance-Space with Diverse and Discriminatory Instances for the Knapsack Problem (2022)
Conference Proceeding
Marrero, A., Segredo, E., León, C., & Hart, E. (2022). A Novelty-Search Approach to Filling an Instance-Space with Diverse and Discriminatory Instances for the Knapsack Problem. In Parallel Problem Solving from Nature – PPSN XVII. PPSN 2022 (223-236). https://doi.org/10.1007/978-3-031-14714-2_16

We propose a new approach to generating synthetic instances in the knapsack domain in order to fill an instance-space. The method uses a novelty-search algorithm to search for instances that are diverse with respect to a feature-space but also elicit... Read More about A Novelty-Search Approach to Filling an Instance-Space with Diverse and Discriminatory Instances for the Knapsack Problem.

How do young students get enthusiastic about computational thinking activities? (2021)
Conference Proceeding
Herrero Álvarez, R., León, C., Miranda, G., Segredo, E., Socas, Ó., Cuellar-Moreno, M., …Díaz, Y. (2021). How do young students get enthusiastic about computational thinking activities?. In EDULEARN21 Proceedings. https://doi.org/10.21125/edulearn.2021.0199

This paper presents a study of the emotions that are produced in pre-university students when performing Computational Thinking activities. In the absence of an official document that deals what content of Computational Thinking should be taught at t... Read More about How do young students get enthusiastic about computational thinking activities?.

A Cooperative Learning Approach for the Quadratic Knapsack Problem (2018)
Conference Proceeding
Lalla-Ruiz, E., Segredo, E., & Voß, S. (2018). A Cooperative Learning Approach for the Quadratic Knapsack Problem. In Learning and Intelligent Optimization Conference (LION12) (31-35). https://doi.org/10.1007/978-3-030-05348-2_3

The Quadratic Knapsack Problem (QKP) is a well-known optimization problem aimed to maximize a quadratic objective function subject to linear capacity constraints. It has several applications in different fields such as telecommunications, graph theor... Read More about A Cooperative Learning Approach for the Quadratic Knapsack Problem.

A novel similarity-based mutant vector generation strategy for differential evolution (2018)
Conference Proceeding
Segredo, E., Lalla-Ruiz, E., & Hart, E. (2018). A novel similarity-based mutant vector generation strategy for differential evolution. In H. Aguirre (Ed.), Proceedings of the Genetic and Evolutionary Computation Conference 2018. https://doi.org/10.1145/3205455.3205628

The mutant vector generation strategy is an essential component of Differential Evolution (DE), introduced to promote diversity, resulting in exploration of novel areas of the search space. However, it is also responsible for promoting intensificatio... Read More about A novel similarity-based mutant vector generation strategy for differential evolution.

The importance of the individual encoding in memetic algorithms with diversity control applied to large Sudoku puzzles (2017)
Conference Proceeding
Segura, C., Segredo, E., & Miranda, G. (2017). The importance of the individual encoding in memetic algorithms with diversity control applied to large Sudoku puzzles. In 2017 IEEE Congress on Evolutionary Computation (CEC). https://doi.org/10.1109/CEC.2017.7969565

In recent years, several memetic algorithms with explicit mechanisms to delay convergence have shown great promise when solving 9x9 Sudoku puzzles. This paper analyzes and extends state-of-the-art schemes for dealing with Sudoku puzzles of larger dim... Read More about The importance of the individual encoding in memetic algorithms with diversity control applied to large Sudoku puzzles.