Methods of Artificial Intelligence

Ute Schmid

Fachgebiet Informatik, FB Mathematik-Informatik, Universität Osnabrück

Kai-Uwe Kühnnberger

Institut für Kognitionswissenschaft, FB Humanwissenschaften, Universität Osnabrück

Vorlesung im Wintersemester 2002/2003
(Lecture in winter term 02/03)

Kategorie: Informatik/Künstliche Intelligenz / Category: Computer Science/Artificial Intelligence

Course Language: English

Themen: Einführung grundlegender Konzepte, Methoden und Algorithmen der Künstlichen Intelligenz mit Bezügen zu kognitionswissenschaftlichen Themen: Problemlösen und Planen, Constrainterfüllung, Theorembeweis und nicht-monotones Schliessen, Ansätze der Wissensrepräsentation, Maschinelles Lernen, deklarative Programmiersprachen. Ausblick auf aktuelle/vertiefende Themen: Multiagentensysteme, kognitive Robotik, Bildverarbeitung, Sprachverarbeitung.
Empf. Semester: 3. Sem. und höher (Voraussetzung: grundlegende Programmierkenntnisse (Info A und/oder Prolog), Logik oder Info D)

Topics: Introduction to basic concepts, methods, and algorithms of artificial intelligence with relations to topics of cognitive science: Problem solving and planning, constraint satisfaction, theorem proving and non-monotonic reasoning, approaches to knowledge representation, machine learning, declarative programming languages. Discussion of current/special topics: Multiagent systems, cognitive robotics, computer vision, natural language processing.
Proposed for students in 3rd or higher semester (prerequisite: basic programming skills (Info A and/or Prolog), Logic or Info D)

Please note: This course is offered by the Institute of Cognitive Science and not by the Computer Science group. Although it mainly addresses cognitive science students, the topic might be of interest for students of Applied System Sciences and bachelor students of Mathematics/Computer Science.

Hours and Contact

Online Information

Credits

Schedule and Syllabus

Practice

• Lecture: DO 10:05-11:35 in 35/E16
  Practice: FR 12-14 in 41/112
• Contact:
  Lecture: Ute Schmid, schmid@informatik.uni-osnabrueck.de
  Practice: Kai-Uwe Kühnberger, kkuehnbe@uos.de
  Tutors: Bernd Pachur (bpachur@uos.de),Collin Rogowski (collin@rogowski.de), Tobias Widdra (tobias.widdra@gmx.de)

• Introductory Text Books and Further Reading:
  • A list of AI text books can be found [here].
    
  • Stuart Russell and Peter Norvig (1995). Artificial Intelligence: A Modern Approach. Prentice Hall.
    The mostly used text book in the field.
  • Nils Nilsson (1998). Artificial Intelligence: A New Synthesis. Morgan Kaufmann.
    Since Nilsson is the inventor of the A*-algorithm, his chapters on heuristic search algorithms are written very clearly and detailed. His most comprehensive text on search methods is: Nils Nilsson (1971). Problem-Solving Methods in Artificial Intelligence, McGraw-Hill.
  • Patrick Winston (1993). Artificial Intelligence. (3rd edition) Addison-Wesley.
    A not very formal book. Its advantage is that it addresses relations to cognitive science research.
  • Günther Görz, Claus Rollinger und Josef Schneeberger (2000). Handbuch der Künstlichen Intelligenz. (3. Auflage) Oldenbourg.
    A detailed overview of topics of AI. Gives an overview of AI-research in Germany.
  • Raymond Kurzweil (1992). The Age of Intelligent Machines. MIT Press.
    This is not a scientific text book but a most motivating, comprehensive book for a broad readership.
    see also [KurzweilAI.Net]
  • Search for scientific papers: [The Collection of Computer Science Bibliographies] [Citeseer]
  • A good resource for logic is: [The Stanford Encyclopedia of Philosophy]
• AI Programming:
  • In the 80ies, the declarative languages Prolog (logic programming) and Lisp (functional programming) were considered as the typical AI languages (5th generation languages). Today AI programming differs no longer from other domains of program/system development. Often, object-oriented languages are used. Nevertheless, logic and functional programming languages still provide a useful approach to modelling and implementation of AI algorithms.
  • Lisp: [Common Lisp the Language, 2nd Edition] [Marty Hall's Collection] [CLisp Home]
  • Functional Programming in general: [see page of the functional programming lecture]
  • Prolog: [see page of the programming in logic lecture]
• Homepage of AAAI and of GI Fachbereich 1 - Künstliche Intelligenz
• [How many AI people does it take to change a lightbulb?] [The Infamous Turing Test Episode]
• Homepage of the lecture of Claus Rollinger in winter term 01/02: Methods of AI 01/02
• Slides of a previous lecture by Ute Schmid: Grundlagen der KI, SS 1998

• Cognitive science students: This course is an elective in AI with 8 credit points.
• Others: This course in an elective in computer science. You can obtain an "Übungsschein" doing the assignements. For an exam the "Übungsschein" is prerequisite.
  For all students needing courses with 6 hours (4 hours lecture and 2 hours practice) it is possible to combine this basic 4 hours course with a specialized 2 hours course (typically a seminar course) in AI.