Artificial Intelligence. ECAI 2023 International Workshops

XAI^3, TACTIFUL, XI-ML, SEDAMI, RAAIT, AI4S, HYDRA, AI4AI, Kraków, Poland, September 30 – October 4, 2023, Proceedings, Part I

Sławomir Nowaczyk, Przemysław Biecek, Neo Christopher Chung, Mauro Vallati, Paweł Skruch, Joanna Jaworek-Korjakowska, Simon Parkinson, Alexandros Nikitas, Martin Atzmüller, Tomáš Kliegr, Ute Schmid, Szymon Bobek, Nada Lavrac, Marieke Peeters, Roland van Dierendonck, Saskia Robben, Eunika Mercier-Laurent, Gülgün Kayakutlu, Mieczyslaw Lech Owoc, Karl Mason, Abdul Wahid, Pierangela Bruno, Francesco Calimeri, Francesco Cauteruccio, Giorgio Terracina, Diedrich Wolter, Jochen L. Leidner, Michael Kohlhase, Vania Dimitrova (Herausgeber)

Buch | Softcover

XIX, 455 Seiten

2024 | 1st ed. 2024
Springer International Publishing (Verlag)
9783031503955 (ISBN)

Infos

This volume constitutes the refereed proceedings presented at the international workshops of the 26th European Conference on Artificial Intelligence, ECAI 2023, which was held in Kraków, Poland, in September-October 2023. The papers in this volume were presented at the following workshops: XAI^3, TACTIFUL, XI-ML, SEDAMI, RAAIT, AI4S, HYDRA, AI4AI.

Produkt-Details

• Erscheinungsdatum: 23.01.2024
• Reihe/Serie: Communications in Computer and Information Science
• Zusatzinfo: XIX, 455 p. 134 illus., 126 illus. in color.
• Verlagsort: Cham
• Sprache: englisch
• Maße: 155 x 235 mm
• Gewicht: 724 g
• Themenwelt: Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
• Schlagworte: Artificial Intelligence • Artificial Intelligence for Sustainability • Autonomous Systems • Data Mining • Decision Making • Deductive and Inductive Reasoning • evolutionary computation • Explainable machine learning • Fairness and Bias in Artificial Intelligence • interpretable machine learning • machine learning • Multi-agent Systems • Reinforcement Machine Learning • Reliability of Artificial Intelligence • Responsible Artificial Intelligence • Semantics • Social Artificial Intelligence • Supervised Machine Learning • unsupervised machine learning • Verification of AI systems
• ISBN-13: 9783031503955 / 9783031503955
• Zustand: Neuware