Advances in Artificial Intelligence Research: Proceedings of the 6th Polish Conference on Artificial Intelligence, PP-RAI 2025, Katowice, Poland, 7-9 April, 2025

by Beata Zielosko (Editor), Rafal Doroz (Editor), Ireneusz Czarnowski (Editor), Janusz Kacprzyk (Editor), Jacek Mandziuk (Editor)

Overview

This book is a collection of papers related to the latest achievements and development trends in the field of artificial intelligence. This compilation of peer-reviewed articles presents both theoretical foundations and innovative algorithms, as well as interdisciplinary applications that shape modern intelligent technologies. It serves as a platform for critical academic discussion, integrating methodological foundations with the analysis of contemporary AI issues.

This book points to many advances topically subdivided into parts related to data mining and machine learning, medical, interdisciplinary and human behaviour applications, neural network and deep learning systems, computer vision, uncertainty in AI, robotics and autonomous systems, problem solving and optimisation, generative AI, decision-making and classification in complex systems, and research of young scientist in field of AI. By addressing innovative approaches, implementation efficiency, and responsibility in applications, this book is a valuable source of knowledge for researchers, practitioners, and students in technical disciplines.

Product Details

ISBN-13:	9783032041968
Publisher:	Springer Nature Switzerland
Publication date:	01/12/2026
Series:	Lecture Notes in Networks and Systems , #1599
Pages:	369
Product dimensions:	6.10(w) x 9.25(h) x (d)

Table of Contents

Part 1.Data Mining and Machine Learning.- 1.Cost-constrained multi-label group feature selection using shadow features.- 2.Enhancing Grammatical Evolution with Neural-Inspired CFG for Explainable AI.- 3.Performance Comparison of Classifiers for Meta Instance Selection.- Part12.Decision-Making and Classification in Complex Systems.- 28.Dynamic Fatigue Prediction in Football: A Deep Learning-Driven Approach to Optimize Performance.- 29.Exploring potential of Expected Solution Point in group decision-making.- 30.Analysis of Ranking Methods and Classifiers for Drift Detection using the Feature-based Drift Detector.