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| TDDA23 | Artificial Intelligence and LISP, 4,5 p (sw) /Artificiell intelligens och LISP/ Advancement level: B | |
| Aim: Advanced data processing, as in Artificial Intelligence (AI) and Expert Systems, is becoming increasingly more common in areas such as decision support, economic analysis, production planning, robot control, construction planning, etc. An understanding of AI is required to be able to use these techniques. We study also the LISP language which is the development language for most AI tools.Prerequisites: Basic courses in computer science and programming (10 credits).Supplementary courses: TDDB 66 Expert System - Methods and Tools.Course organization: The course comprises two parts - Lisp and AI. The lectures on Lisp aim to present the language and its underlying philosophy. The tutorials provide practice and preparation for the laboratory work. The lectures on AI present the basic theory and various applications. The laboratory work involves implementation of AI techniques.Course content: Part 1. The LISP programming language: language and programming environment, such as editor, break and file management; methods for interactive, incremental program development. Part 2. Overview of AI: Problem characteristics and applications. Basic problem-solving methods: state space search, resolution and predicate logic and structured knowledge representation. Applications: planning, natural language processing, machine learning and robotics.Course literature: Dean, T., Allen, J., Aloimonos, Y., Artificial Intelligence - Theory and Practice, Benjamin/Cummings, 1995. Compendium compiled at the Department of Computer and Information Science | ||
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