On measuring and improving the quality of linkage learning in modern evolutionary algorithms applied to solve partially additively separable problems. - Michal Witold Przewozniczek; Bartosz Frej; Marcin M. Komarnicki (GECCO, 2020)

Hybrid linkage learning for permutation optimization with Gene-pool optimal mixing evolutionary algorithms. - Michal Witold Przewozniczek; Marcin M. Komarnicki; Peter A. N. Bosman; Dirk Thierens; Bartosz Frej; Ngoc Hoang Luong (GECCO Companion, 2021)

Direct linkage discovery with empirical linkage learning. - Michal Witold Przewozniczek; Marcin Michal Komarnicki; Bartosz Frej (GECCO, 2021)

On turning black - into dark gray-optimization with the direct empirical linkage discovery and partition crossover. - Michal Witold Przewozniczek; Renato Tinós; Bartosz Frej; Marcin M. Komarnicki (GECCO, 2022)

The hop-like problem nature - unveiling and modelling new features of real-world problems. - Michal Witold Przewozniczek; Bartosz Frej; Marcin M. Komarnicki (CoRR, 2024)

Availability of Perfect Decomposition in Statistical Linkage Learning for Unitation-based Function Concatenations. - Michal Prusik; Bartosz Frej; Michal Witold Przewozniczek (CoRR, 2025)

From Direct to Directional Variable Dependencies - Nonsymmetrical Dependencies Discovery in Real-World and Theoretical Problems. - Michal Witold Przewozniczek; Bartosz Frej; Marcin Michal Komarnicki (IEEE Trans. Evol. Comput., 2025)