| Kurzkommentar |
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 satisfiability, 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/ML offered at UdS or to write their Bachelor or Master thesis in the field of AI.
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