Master Thesis: “Goal Reasoning and Action Planning under Dynamics and Uncertainty”

Exogenous changes, sensing information and human-robot interaction turn plan generation and execution for autonomous intelligent agents into inherently dynamic and recurring tasks. First of all, multiple and sometimes conflicting goals need to be prioritized, where the success chances of plans for achieving the goals need to be taken into account. Moreover, plans may be based on sensing information, where the information acquisition and predictive evaluation of possible outcomes must be incorporated into the planning process. In multi-agent decision making, which particularly includes human-robot collaboration, reasoning about the capabilities, knowledge and goals of other agents is important to coordinate joint operations. Last but not least, real-world scenarios are subject to exogenous and often unpredictable changes in the environment; e.g., autonomous vehicles must constantly monitor the traffic to take safe actions.

In the light of these challenges, the goal of the Master thesis is to develop a demonstrator for dynamic goal reasoning and action planning in a selected application scenario from the robotics domain. The Master thesis will be co-supervised by members of the Department of Artificial Intelligence and Cybersecurity at the University of Klagenfurt and the JOANNEUM RESEARCH Robotics Institute at the Lakeside Science & Technology Park. This collaboration offers a unique opportunity to showcase Artificial Intelligence methods for planning and optimization in a practically relevant robotics environment, set up in simulation or even physically.

The following are some (incomprehensive) literature references, which can be consulted as a starting point for getting better intuition of the Master thesis topic and relevant research targets:

  • M. Rizwan, V. Patoglu, E. Erdem. Human Robot Collaborative Assembly Planning: An Answer Set Programming Approach. Theory and Practice of Logic Programming, 20(6): 1006-1020, 2020. https://arxiv.org/abs/2008.03496
  • B. Schäpers, T. Niemueller, G. Lakemeyer, M. Gebser, T. Schaub. ASP-Based Time-Bounded Planning for Logistics Robots. International Conference on Automated Planning and Scheduling, 2018. https://www.aaai.org/ocs/index.php/ICAPS/ICAPS18/paper/download/17777/16944
  • P. Mazdin, M. Barcis, H. Hellwagner, B. Rinner: Distributed Task Assignment in Multi-Robot Systems based on Information Utility. International Conference on Automation Science and Engineering, 2020. https://ieeexplore.ieee.org/document/9216982
  • B. Reiterer, M. Hofbaur. Opportunistic Planning with Recovery for Robot Safety. German Conference on Artificial Intelligence, 2017. https://link.springer.com/chapter/10.1007/978-3-319-67190-1_31

The Master thesis topic is suitable for students of Applied Informatics, Artificial Intelligence and Cybersecurity, Information Technology or Information Management. For further information, please contact Univ.-Prof. Dr. Martin Gebser (Martin [dot] Gebser [at] aau [dot] at), research group for Production Systems.

Hello from the Cybersecurity research group!

Established within the university’s Digital Age Research Center (D!ARC) the Cybersecurity research group goes into it’s second year of activities. The group’s research areas are based within cryptography, statistical machine learning, embedded security, artificial intelligence and deep learning as well as crypto engineering.

The group’s main expertise is in the area of deployment aspects of cryptography. Such aspects are related to information leakage (via side channels), and the detection and prevention of such channels; practical cipher constructions for specific application areas; secure implementation techniques and tools; and the application of machine learning and deep learning in the context of cybersecurity.

The Cybersecurity research group is currently running an ERC funded Consolidator Grant project, titled SEAL („Sound and Early Assessment of Leakage for Embedded Software“). It tackles the challenge to developed tools that are sophisticated enough to predict a range of side channel leakage behaviours for modern processors.

In the last months the team has grown to the number of ten. Currently the group consists of one professor, one lecturer, three postdocs, three PhD students, one technician and one administrator. The group represents five different countries, making work and communication a truly international and cultural experience.

You will find more information here:
www.aau.at/digital-age-research-center/cybersecurity/

And here:
www.cybersecurityresearch.at/

If you are interested to explore collaborations in any shape or form, let’s talk!
Please email to Elisabeth [dot] Oswald [at] aau [dot] at

 

 

 

Studienassistenz (7h/Woche) gesucht !!!!

Die AAU Klagenfurt / TeWi – Abteilung Artificial Intelligence und Cybersecurity – sucht ab März 2021 eine Studienassistentin (7 h/Woche).

Aufgaben:

Umstellung der PPTX-Folien von Systemsicherheit auf LaTeX und Erweiterung und Pflege der SPU-Fragen für “Algorithmen und Datenstrukturen”, “Einführung in die theoretische Informatik” und “Systemsicherheit”

Erwünscht sind:

– Deutschkenntnisse

– Genauigkeit

– Verlässlichkeit

– Organisationstalent und die Bereitschaft zur raschen Einarbeitung.

Formlose Bewerbungen an Peter Schartner erbeten.

From Applied Informatics to Artificial Intelligence and Cybersecurity

From January 1, 2021, we have changed our official name into Department of Artificial Intelligence and Cybersecurity. The old name (Department of Applied Informatics) was somewhat unspecific, and the new name should reflect the majority of work carried out at the department. The downside is of course that it does not perfectly cover all activities that are going on (but also in the past the department had some significant theoretical output, despite its name).
Maybe you have noticed that there is a new MSc programme of the same name (https://www.aau.at/en/studien/master-artificial-intelligence-and-cybersecurity/) – the interesting bit is that the same name was suggested independently for these two entities, but the department is also the main driving force behind the programme.