Department of Computer Science
CS 785 Knowledge Acquisition and Problem Solving
Meeting time: Thursday
Meeting location: IN 209
Prerequisite: an introductory course in artificial intelligence.
The objective of this course is to present the principles and major methods of knowledge acquisition for the development of knowledge-based agents that incorporate the problem solving knowledge of a subject matter expert. Major topics include: overview of knowledge engineering; analysis and modeling of the reasoning process of a subject matter expert; ontology design and development; rule learning; problem solving and knowledge-base refinement. The course will emphasize the most recent advances in this area, such as: agent teaching and learning; mixed-initiative knowledge base refinement; knowledge reuse; frontier research problems.
The students will learn about all the phases of building a knowledge-based
agent and will experience them first-hand by using the Disciple agent
development environment. Disciple has been developed in the Learning Agents Center of
Exam – 50%
Agent development – 50%
Tecuci G., Lecture Notes on Knowledge Acquisition and Problem Solving, Fall 2004, available online (required).
Tecuci G., Building Intelligent Agents: An Apprenticeship Multistrategy Learning Theory, Methodology, Tool and Case Studies, Academic Press, 1998 (recommended).
Additional papers recommended by the instructor.
Lecture Notes on Knowledge Acquisition and Problem Solving
The Disciple-RKF Learning and Reasoning Agent, Research Report (submitted for publication), 9-16-04 (Optional reading)
4.1 Demo: Using the modeling advisor of Disciple, 10-21-04
6. Agent problem solving, 10-21-04
7. Agent teaching and multistrategy learning, 10-21-04
9. Scripts development for scenario elicitation.
10. Discussion of frontier research problems.
Project Notes on Building an Assistant for Selecting Ph.D. Dissertation Director
Assignment 1, deadline 9-9-04
Problem introduction, 8-27-04
Classification of factors to consider for selecting a Ph.D. Dissertation Director, 9-10-04
Preliminary modeling of reasoning for advisor selection, and Assignment 2, 9-24-04 (Assignment deadline: 10-12-04)
Ontology specification and Assignment 3, 10-21-04 (Assignment deadline:10-28-04)
Teaching and learning - Assignment 4, 11-8-04 (Assignment deadline: 11-11-04 to do part of it; 11-18-04 to complete it).
Knowledge Base Refinement - Assignment 5, 11-15-04 (Assignment deadline: 11-18-04 to do part of it; 12-2-04 to complete it).
Content of project deliverable, 11-24-04