CS 785 Intelligent Computer Interfaces
Note: Based on CS 685 currently in the calendar.
Faculty who are interested in teaching this course:
Robin Cohen, Nick Cercone, Chrysanne Di Marco.
Objectives
To cover subtopics in artificial intelligence that go beyond the syllabus
of an introductory course. To address the topic of designing intelligent
interfaces, including an overview of
higher level natural language processing techniques of particular
value in the construction of interfaces,
models of plan recognition, discourse and natural language generation,
and user modeling.
To expose students to a variety of intelligent system applications
currently being explored in the field, including agents and multi-agent
systems, data mining and information retrieval, case-based reasoning
and intelligent tutoring. To provide students with an overview of
the subtopics of the course as well as exposure to current research
papers, with an aim to developing skills in presentation of research,
critical analysis of research and contribution of original thought.
Intended Audience
This is a course for CS graduate students, definitely including
students in subareas of CS other than artificial intelligence.
Related Courses
CS486 (Logical Methods in AI) would be desirable but is not required.
Some of the introductory lectures in the course help to get students
up to speed in the background.
References
Series of papers which provide an overview of each course topic.
Set of research papers determined by instructor which students select to
present as part of course requirements.
Current Recommended Reading: "Readings in Agents" edited by Huhns and Singh,
Morgan Kaufmann, 1998.
Schedule
3 hours per week - typically 2 hour lecture and 1 hour of paper
presentations by students to compliment the lecture material.
Normally offered in alternate years.
Outline
Introduction (4 hr)
Overview of the course objectives including brief introduction to
each of the course subtopics. Overview of artificial intelligence
including the concepts of structured knowledge representation and
planning. Discussion of the themes of intelligent interfaces
and intelligent systems and their interrelationship.
Intelligent Interfaces (14 hrs)
Overview of natural language processing: syntax, semantics and pragmatics.
Plan recognition. Models of discourse. Natural language generation.
User Modeling. Paper presentations on the topics of plan recognition,
discourse, generation and user modeling.
Intelligent Systems (14 hrs)
Agents (personal digital assistants) and multi-agent systems.
AI approaches to data mining and information retrieval applications.
Case-based reasoning and knowledge-based systems. Intelligent tutoring
systems. Paper presentations on agents and multi-agent systems;
on data mining and information processing; on case-based reasoning and
knowledge-based systems; on intelligent tutoring systems.
Current software systems for these intelligent applications.
Course Conclusion (7 hrs)
Project presentations to provide an overview of current research
topics and directions. Wrap-up of course; summary of lessons learned.