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| TDDA13 | Artificial Intelligence , 3,5 p (sw) /Artificiell intelligens/ Advancement level: B | |
| Aim: The course gives an introduction to artificial intelligence (AI) and its applications. Focus is on developing intelligent agents systems that can decide what to do and do it. This requires techniques for problem solving, knowledge and reasoning, learning, communication, perceiving and acting.Prerequisites: TDDB 92 Programming in Incremental Systems TATM 90 Discrete Mathematics and Logic TDDB 25 Programming: Abstraction and Modelling TDDB 57 Data Structures and AlgorithmsSupplementary courses: TDDA 14 AI Programming TDDB 66 Expert Systems - Methods and ToolsCourse organization: The course consists of 36 hours of lectures and 24 hours laboratory work. Lectures are devoted to theory; AI techniques are practised in the laboratory work.Course content: Overview of AI and its applications. Search as a problem-solving method. Logic as a means of representing knowledge. Reasoning with incomplete information; nonmonotonic and probabilistic reasoning. Structured knowledge representation. Action planning for robots. AI methods in natural language processing. Strategies for automatic learning. Orientation in architectures for AI.Course literature: Russel, S and Norvig, P., Artificial Intelligence, A Modern Approach, Prentice Hall, 1995 Compendium compiled at the Department of Computer and Information Science. Reference literature: Barr & Feigenbaum, The Handbook of Artificial Intelligence, Vols. 1-4, 1981-1989. Charniak, E, McDermott, D, Introduction to Artificial Intelligence, Addison Wesley, 1985. Genesereth, M, R, Nilsson, N,J, Logical Foundations of Artificial Intelligence, Morgan Kaufmann, 1988. Rich, E, Knight, K, Artificial Intelligence, second edition, McGraw Hill, 1991. Shapiro, C, Encyclopedia of Artificial Intelligence, Vol. 1-2, Wiley International. 1991 | ||
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