| Related sites for http://www.cs.northwestern.edu/~forbus/index.html |
| Galassi,_Ugo University of Eastern Piedmont. User profiling, hierarchical HMMs, learning regular expressions. | | Geczy,_Peter RIKEN Brain Science Institute. Neural networks, artificial intelligence, neuroscience, fuzzy logic, rule acquisition, rule extraction from neural networks, Autonomous Connectionistic Engine (ACE), neu | | Gini,_Maria University of Minnesota. Distributed intelligence, cooperation of miniature robots, robot navigation, multi-agent systems for e-commerce and supply-chain, economic agents. | | Goel,_Ashok_K_ Georgia Tech. Knowledge-based reasoning and learning, design cognition and computing, creativity, self-adaptation. | | Goyal,_Ram_Dayal Intigma India. Data mining, natural language processing, data mining, neural networks, image processing. | | Grasso,_Floriana University of Liverpool. Computational models of natural argument, affective natural language generation, conflict resolution. | | Green,_Nancy University of North Carolina at Greensboro. Intelligent multimdedia presentation systems, argumentation models, automatic generation of textual summaries of graphs, interactive narrative, conversati | | Greening,_Dan_R_ CEO BigTribe. Entrepreneur and researcher. Personalization, collaborative filtering, computer-supported cooperative work, ubiquitous computing, simulated annealing, distributed computing, social psych | | Grosz,_Barbara Harvard University. Collaborative planning, SharedPlans model of collaboration, discourse structure, intonation, centering. | | Guinn,_Curry_I_ University of North Carolina at Wilmington. Natural language processing, spoken dialog systems, conversational agents, affective computing. | | Guvenir,_H__Altay Bilkent University. Machine learning, data mining, and computer-aided language learning. | | Haller,_Susan University of Wisconsin - Park. Natural language processing, interactive discourse, text planning, intelligent tutoring systems. | | Harmelen,_Frank_van Vrije Universiteit, Amsterdam. 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|
Kenneth D. Forbus
Kenneth D. Forbus
Walter P. Murphy
Professor of Computer Science
and Professor of Education
Email: forbus <the at sign> northwestern <the usual> edu
Voice: (847) 491-7699
Fax: (847) 491-5258
EECS Department
Northwestern University
Ford 3-320
2133 Sheridan Road
Evanston, IL, 60208
Please note: The Computer Science Department is now part of the Electrical
Engineering and Computer Science Department. I am currently the head of
the Cognitive Systems Division, which is housed in the Ford Engineering
Design Center.
Research Interests
In artificial intelligence, specifically qualitative reasoning, spatial
reasoning, analogical reasoning and learning, learning from natural language, sketch
understanding, and inference engine design.
In cognitive science, understanding how analogy and similarity work,
including the roles they play in cognitive and perceptual processes. We are developing the Companion
cognitive architecture to explore the hypothesis that analogical processing
is at the core of human cognition.
In education, using AI techniques to create new types of educational
software and activities.
In human-computer interaction, the use of sketching as an interface modality
to knowledge-rich systems, and the use of natural language processing with simplified
English to interact with intelligent systems and reduce tailorability in
cognitive simulation.
In computer game design, the roles AI, and especially articulate software,
can play in creating better game engines and synthetic characters.
For more information, including descriptions of ongoing projects, please see
our group's web page, and also
the CogSketch
page at the Spatial Intelligence and
Learning Center.
Teaching
My normal teaching schedule looks like this:
Fall: Cognitive Science 207,
Introduction to Cognitive Modeling. This is the first course in Cognitive
Science. It does not require programming at all. Instead, you'll be
using some off-the-shelf AI systems as a way to get experience with cognitive
modeling. Ultimately, I think it useful for every cognitive scientist to
have some programming experience, but not for the reason you might think.
It's not about writing code per se, but about understanding how to think
procedurally. One of the insights that the field of Cognitive Science is
founded on is the idea that minds are a kind of computation. So
computation is actually one of the languages for expressing theories, not just
a means of simulation. It's hard to get certain intuitions about
computation without programming, but that can come later, if you decide that
you're deeply interested in the field.
Winter: I alternate between two advanced AI courses:
EECS 344: Design of Computer Problem Solvers.
EECS 395: A knowledge representation course.
Both of these courses are taught studio-style, using a combination of
lecture and hands-on work. I think ultimately all courses with a serious
programming component will be taught this way. However, evolving a method
of studio instruction that works for computer science is still very much an
ongoing effort.
If you are interested in Artificial Intelligence, you really should take
both of these courses. There is a lot of programming in 344, in Common
Lisp, so taking EECS 325 at the same time or even before is a good idea.
Spring: I typically alternate between two interactive
entertainment courses, which is one of the focal areas of our division:
EECS 370-0
Computer Game Design
Fundamentals of computer game design. Topics include: Plot, narrative
and character, simulation for creating game worlds, AI for synthetic
characters, tuning gameplay. Substantial programming and project work.
Prerequisites: 725-311, plus at least one of 725-322, 725-343, 725-348, or
725-351.
EECS 392-22: Artificial
Intelligence for Interactive Entertainment. This is an experimental
course, which will cover both the kinds of AI techniques used in strategy games
and the application of advanced natural language and reasoning technology to building
new kinds of conversation-oriented entertainment systems. The poster for
the course is here.
For 2008-2009: It's
CogSci 207 for Fall, EECS 395-Knowledge Representation for Winter, and EECS 370
for Spring.
Advising
If you are one of my advisees, please look here.
Miscellaneous
Ultimately,
building computer models will, I suspect, become a popular
hobby. However, there are a number of technical
problems that must be overcome before this happens.
My old web
page provides an ancient capsule summary of my research interests.
A friend
from Belize
On DARPA
duty
Last edited 8/13/08, by KDF.
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