Rough Sets were introduced by Zdzisław Pawlak in the early ’80s and developed further as a method of knowledge representation and processing based on uncertain data and incomplete information. Nowadays, Rough Set theory is widely recognized to have great importance in several fields, including artificial intelligence, mathematics, knowledge representation and machine learning, as evidenced by the increasing number of works concerned with its applications and theoretical foundations.

The 11th International Conference on Pattern Recognition and Machine Intelligence (PReMI'25) December 11-14, 2025, Indian Institute of Technology, Delhi, India https://premi25.iitd.ac.in/