Artificial Intelligence (Summer Semester, jointly with Professor Jörg Hoffmann)

This course offers a general introduction into the field of Artificial Intelligence (AI), its history, key assumptions, paradigms, concepts, and fundamental methods. Students learn to master and apply techniques developed in the fields of intelligent agents, search algorithms and game playing, knowledge representation, logical reasoning and deduction, planning, constraint reasoning, machine learning, and reasoning under uncertainty. We explain how and when these methods work and for which problem classes they are suitable to successfully build AI systems. With the knowledge acquired in this course, students are well-prepared to successfully attend the many special lectures on AI offered at UdS or to write their Bachelor or Master thesis in the field of AI.

Latest publicly available lecture materials

Architectural Thinking for Intelligent Systems (Winter Semester)

This course teaches established and successful methods of modern architectural thinking, which are applied by software architects for the systematic planning, conception, and evaluation of complex software (and hardware) architectures. Examples are taken from the context of intelligent systems, where AI technology needs to be integrated into often complex hardware and software environments. Starting from an initially vague understanding of the system to be built, we systematically refine our understanding by asking the right questions, developing a vision, applying architectural styles and pattern, minimizing risks, and evaluating the outcome of architectural decisions.

Latest publicly available lecture materials


Bachelor and Master Thesis Projects

The main focus of the AI chair is on optimization problems solved using AI CP/SAT solvers or reinforcement learning. We are especially interested in the intelligibility of models and in methods to make modeling optimization problems easier. Furthermore, we are interested in reference architectures for intelligent systems. Apart from these areas, we are also open to your suggestions for topics.

Below you find our current suggestions for thesis projects for the winter term 2021. For each topic, we give a profile indicating if the work is more on the conceptual or practical level, or a combination of both. You also see which topics are available for Bachelor/Master theses.

Please apply with a short CV, your transcript of records, and by relating to one of the topics below or by proposing an own project, describing own ideas in a short paragraph.

AIden Teaching Assistant Extension

The AI lecture at UdS is supported by a variety of digital resources including 1500 pages of slides and video recordings of all lectures. The Chatbot AIden (https://aiden.cs.uni-saarland.de/) supports students in searching the vast amount of content and working more effectively on exercises. To fulfill those tasks AIden uses multiple Google Cloud services like Google Dialogflow for the intent recognition and different transformation functions like the Google Video Intelligence Cloud or the text-to-speech service.

Several subprojects are available to extend and improve the current system:

  • You port AIden to AI cloud services from Amazon and Microsoft and you conduct a thorough evaluation in your thesis to compare AI services from different platforms. The goal of your thesis is an evaluation methodology for search-oriented chatbot solutions using cloud services.
  • AIden currently runs on a university server at UdS. Alternative hosting models are available for example via Google Cloud or Amazon AWS. You implement different hosting models and compare them to each other. The goal of your thesis is to provide facts for architectural decisions concerning the infrastructure and operational model of chatbot solutions.
  • A still neglected quality criterion for AIden is testability. To address testability, your thesis develops a test strategy for the system including whitebox testing of own components and blackbox testing of AI cloud services. You improve the current architecture wrt. testability and also to remove any detected faults. The goal of your thesis is to develop a quality tactics for the testability of a project using AI cloud services, see also the testability chapter in Software Architecture in Practice by Bass et al. – available at the computer science library.

You must have passed the AI lecture at UdS with good results to apply for this project.

Profile: practical, Bachelor/Master

A Blackboard for the multi-car elevator control system

Multi-car elevator systems consist of several autonomous cabins that transport passengers in a system of transportation shafts of flexible layout. A complex state representation serves as the central data-centric integration component of the multi-car elevator system, which holds information about the cabins, e.g., their positions, door states, currently planned stops for each cabin, and building information like the number of floors. The dynamic information in this state representation highly depends on the current calls by passengers and strategies to answer them. In this thesis, you explore how such complex state representation can be implemented using the Blackboard architectural style to support distributed problem solving by AI agents. The goal of your thesis is an implementation of the blackboard based on an existing code base for the multi-car elevator system in C#, which also provides you with several agent implementations to compute the lift control.

Profile: practical, Master/Bachelor

Recognizing Hard Problem Instances

Whereas NP-complete problems are considered “hard”, there are many easy-to-solve instances of NP-complete problems, i.e., they can be solved in a short time. It is conjectured that all NP-complete problems have at least one parameter describing how constrained a problem instance is and that the hard to solve instances are around a critical value of this parameter, see “Where the really hard problems are” by Peter Cheeseman, Bob Kanefsky and William M. Taylor.

The goal of your thesis is to determine such a parameter for the Cable Tree Wiring problem (“Cable Tree Wiring – Benchmarking Solvers on a Real-World Scheduling Problem with a Variety of Precedence Constraints” by Jana Koehler et.al.). You run experiments with constraint solvers such as IBM Cplex CP and Google OR-Tools to measure the influence of a parameter and you also conduct theoretical analyses to confirm a parameter or to find alternative parameter candidates.

Profile: conceptual/practical, Master/Bachelor

The Traveling Salesman Problem with Time Windows

Given a set of cities and distances between each pair of cities, the Traveling Salesperson problem is the problem of finding the shortest route visiting each city exactly once. It is an NP-hard problem and one of the most famous problems in combinatorial optimization. Today, many variants of this famous problem have been introduced in the literature. In this project, we study the TSP problem with time windows where a city has to be visited during a certain time period or at a certain time point.

The goal of your thesis is to conduct a thorough literature search and review of scientific paper published on this TSP variant since 2010. The goal of your thesis is to develop a classification scheme, which provides a systematic overview on subclasses of TSP problems with Time Windows and makes it possible to compare the various subclasses with each other.

Profile: conceptual, Master