The following fields are treated within the scope of the course: problem-solving with search algorithms, heuristics, knowledge representations (logic), planning, representation of uncertainty and inference (Bayesian networks, HMM), decision theory and utility theory, diction (NLP).
After passing the course, the student shall be able to:
- apply different principles of Artificial Intelligence (AI)
- choose appropriate tools and implement efficient solutions to problems in AI
- integrate tools to design computer programs that show different properties that are expected by an intelligent system
- present, analyze, and entitle your own solution to an AI problem
- reflect on and discuss current social and ethical aspects of AI
To be able to:
- draw use of methods of artificial intelligence in the analysis, design, and implementation of computer programs
- contribute to designing an intelligent system in academic and industrial applications.