NLP+ASR+CAI (natural language processing, automatic speech recognition, and conversational AI)
- Chair: Maciej Piasecki, Wrocław University of Science and Technology
CV (computer vision)
- Chair: Leszek Chmielewski, Warsaw University of Life Sciences
The session is organized in cooperation with the Institute of Information Technology, Warsaw University of Life Sciences - SGGW, the Association for Image Processing, Poland – Towarzystwo Przetwarzania Obrazów and the Section of Multimedia, Committee on Informatics of the Polish Academy of Sciences.
KE (knowledge engineering)
Co-Chairs:
- Agnieszka Lawrynowicz, Poznań University of Technology
- Grzegorz Nalepa, Jagiellonian University
- Dariusz Krol, Wrocław University of Science and Technology
Neural Network and Deep Learning Systems
Co-Chairs:
- Aleksander Byrski, AGH University of Science and Technology
- Marcin Kurdziela - AGH University of Science and Technology
Data mining and Machine Learning
Co-Chairs:
- Jerzy Stefanowski, Poznan University of Technology
- Michał Woźniak, Wrocław University of Science and Technology
PS+O (problem solving and optimization)
- Chair: Ewa Bednarczuk, Warsaw University of Technology and Systems Research Institute Polish Academy of Sciences
NI (neuroinformatics)
Co-Chairs:
- Włodzisław Duch, Nicolaus Copernicus University in Toruń
- Juliusz Szymański, Gdańsk University of Technology
The session is organized in cooperation of Nicolaus Copernicus University in Toruń And Gdańsk University of Technology.
UAI (uncertainty in artificial intelligence)
- Chair: Dominik Ślęzak, University of Warsaw
The track aims at discussing various approaches to dealing with the uncertainty in a broad range of AI systems and applications. The uncertainty can refer to indeterminism, incompleteness, vagueness, and many other aspects related to knowledge, information, and data. Its models and representations have been recently widely discussed in the area of machine learning, stating one of important connections between AI and ML. The elements of reasoning under uncertainty can be found in many practical fields, such as robotics, simulations, agent systems, information integration, video game industry, and so on. Accordingly, there are many methodologies of working with the uncertainty, relying on probabilistic models (such as e.g. Bayesian networks), fuzzy sets, rough sets (particularly rough set approximations), information granulation, and many others. This year it is especially worth referring to the UAI methods originating from the theory of rough sets, given its 40th anniversary. Therefore, the UAI track will be coordinated closely with the rough set anniversary panel session and the contest held at PP-RAI'22.
RAS ((R)obotics and (A)utonomous (S)ystems)
- Chair: Piotr Skrzypczyński, Poznan University of Technology
One of the thematic threads (tracks) of PP-RAI - since the first edition - is Robotics and Autonomous Systems. This is a subject area devoted to the application of methods and algorithms that belong to the broadly understood artificial intelligence in robotics and related areas (autonomous vehicles, biocybernetics, human-machine interfaces, image processing in technology and industry and various types of personalized agents). Artificial intelligence methods and algorithms, especially machine learning methods, are key factors in the progress of modern robotics. At the same time, many initiatives (e.g. the Horizon Europe framework programs of the European Commission) emphasize the need for cooperation of various environments drawing on the achievements of AI and able to contribute to its development and implementation in the economy. Therefore, we invite you to submit works for PP-RAI 2022 in RAS track. Papers in the form of extended abstracts of 4 pages (in English) should be submitted as required by PP-RAI. Deadline for submitting works ends February 28, 2022
Multiagent systems
- Chair: Jarosław Wąs, AGH Univeristy of Science and Technology
AI Tech space
- Chair: Jacek Rumiński, Gdańsk University of Technology
The track is dedicated for submitions of abstracts or papers containing the results of research conducted as part of the AI Tech project.
Young.AI (session for young researchers)
- Chair: Agnieszka Lazarowska, Gdynia Maritime University
This track is an opportunity for young researches and students to present their ideas, methods, solutions and applications making use of artificial intelligence. The topics of interest include, but are not limited to, the following themes: machine learning, neural networks and deep learning, fuzzy logic and fuzzy systems, multi-agent systems, robotics, autonomous systems, expert systems, evolutionary computation, reasoning, knowledge representation, planning, learning, natural language processing, perception. The track will constitute a forum of thoughts, ideas and experiences exchange, especially intended for young scientists, so the concepts related to AI at different stages of their development, from very initial phase, through the development stage, up to the final stage of implementation and testing, are all warmly welcomed.
