Artificial Intelligence Group
Dept of Computing Science
University of Alberta
Edmonton, Alberta
http://www.cs.ualberta.ca/~ai
The University of Alberta has a large and active group of AI researchers, whose interests span the
breadth of Artificial Intelligence, including learning, games, natural language, constraint satisfaction,
agents, and representation and reasoning; see the research profiles shown below.
(This is
complemented by a large group of researchers working in vision, pattern recognition, robotics, and
other related activities.) Our results include both theoretical investigations and empirical studies,
often in collaboration with companies (including BioTools, CELcorp, CN Rail, Electronic Arts,
Syncrude, Siemens). Many of our members sit on editorial boards of major journals and societies.
We are currently producing an on-line interactive encyclopedia ("All About AI"). Moreover, we
(Edmonton and UofAlberta) will host AAAI in 2002.
We are currently looking for new
graduate students
http://www.cs.ualberta.ca/programs/graduate/
post-docs
http://www.cs.ualberta.ca/jobs/postdoc.html
faculty (all levels)
email:everitt@cs.ualberta.ca
Please contact us if you are interested.
All About AI:
A
well-crafted
handbook,
which
provides
authoritative and up-to-date surveys across the
subareas of the discipline, is a tremendous asset to a
field: It is an invaluable aide to both researchers and
teachers, and also an effective window for both the
lay public, and funding agencies, to see the best and
most interesting work the field has to offer. The "All
About AI" project is providing such a resource, with
up-to-date scholarly articles, augmented with
interactive demos, videos, etc, covering the breadth
of Artificial Intelligence topics. These articles will be
written by the experts in the areas, then rigorously
reviewed and edited, and augmented with
appropriate multimedia components.
See http://www.cs.ualberta.ca/~aiexpl
Vadim Bulitko
I am interested in so-called the strong AI including
Machine Learning and Automated Decision Making.
My foci include using network formalisms such as
extended Petri Nets for envisionment based
scheduling as well as using blackboard architectures
for real-time problem-solving and intelligent
tutoring. My mathematical interests are centered
around oracle computations and the Recursion
Theory. My projects to date have included
automated decision support and intelligent tutoring
for Navy ship damage control as well as anomaly
detection for oil mining operations. Current projects
involve automated forestry inventorization using
aerial imaging.
Terry Caelli
In general, my interests lie in the development of
active, intelligent human-machine interaction
systems technologies which use sensing, signal
processing and Artificial Intelligence techniques to
build computing systems of the future. Currently I
am working on two major areas: Image
interpretation and GIS, and Learning, recognizing
and predicting complex human actions.
Renée Elio
My current work focuses on the application and
extension of multiagent communication theory and
practice to the design of systems that engage in
cooperative tasks with a human user or user-agent.
This project has a number of research directions,
including user modeling via learning techniques and
integration with current proposals for standardized
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agent communication languages. My other research
areas concern belief revision and plausible inference,
i.e., how an intelligent agent resolves contradictions
and moves to new situational models using
incomplete and imperfect information. From a
cognitive sciences perspective, I integrate aspects of
formal models of reasoning and inference from AI
and philosophy with empirical data and theories
from cognitive psychology
Randy Goebel
My current research focuses on the development and
application of non-deductive reasoning techniques
(non-monotonic reasoning and belief revision) and
their application to automated diagnosis, scheduling,
database mining, and related areas. The challenge is
to retain the clarity and robustness of good theory,
while making progress in their practical deployment
in real applications.
The current most active application areas are
intelligent scheduling, automated layout, and data
base mining. The methods for scheduling and layout
are based on extensions of the theory and practice of
constraint
solving
and
constraint
logic
programming. In both cases, there exist important
and difficult challenges with respect to the
incremental specification of complex scheduling and
layout constraints, and the incremental dynamic
specification of optimization criteria.
Russ Greiner
I am interested in building algorithms that learn
from experience, to be able to perform their tasks
better. Many of my research results extend standard
learning algorithms and analyses to produce more
robust and more effective learning systems. These
include learning techniques that make efficient use
of the training sample (e.g. by observing training
samples sequentially rather than in batch, or by
using a partially specified sample); by learning
optimal active classifiers and by exploiting known
domain and other relevant information, such as how
the learned system will later be used.
Ryan Hayward
I'm mainly interested in algorithms for discrete
and/or combinatorial problems, especially graph
algorithms; within AI, I'm interested in any
problems to which such discrete/combinatorial/
graph theoretic algorithms apply. Current areas of
interest include algorithms for board games (hex,
lines of action, etc.), and algorithms which minimize
the expected cost of boolean expression evaluation.
Dekang Lin
My research area is Natural Language Processing
known as Computational Linguistics). I am
interested in parsing, acquisition of lexical
knowledge, coreference resolution, word sense
disambiguation, and question-answering.
Tony Marsland
The dual interest in artificial intelligence and
distributed computation comes through the study of
tree-searching methods that prune unimportant
branches during the search process. A primary aim is
to develop an understanding of the problem-solving
and planning aspects of human intelligence. Another
aim is to develop distributed solutions to help with
the planning component of searching. The latter
work usually involves the development of better
load balancing strategies for multi-computers.
Francis Jeffry Pelletier
I investigate semantic formalisms for knowledge
representation, automated reasoning, computational
linguistics, and cognitive science. I have developed a
large-scale automated reasoning system employing
natural deduction techniques to construct proofs for
problems stated in "natural form" in predicate logic
with identity. It has been extended in two different
ways to deal with non-classical logics: (a)
"translation into the semantic metatheory" generates
"indirect" proofs of problems in all normal modal
logics and some relevance logics, and (b) many
normal modal logics have been treated by
incorporating actual inference rules into the theorem
prover. I have also investigated the linguistic and
semantic behavior of "generic statements" such as
Potatoes contain vitamin C. These statements are
interesting because they can be true while
nonetheless admitting exceptions. Considerations of
this logical behavior have given rise to nonmonotonic logics as a way to deal with these
peculiarities, which in turn has suggested the notion
of belief revision as a more inclusive account of this
logical behavior.
Jonathan Schaeffer
I am interested in anything to do with single-agent
(A*) and two-player (alpha-beta) heuristic search. I
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am the author of the program Chinook, the World
Man-Machine Checkers Champion. Chinook has
been recognized by the Guiness Book of World
Records as the first computer to win a human world
championship in any game. We are currently
working on building a program to solve Sokoban
problems. We are currently working on building a
world-class poker-playing (Texas Hold'em) program.
Oliver Schulte
My main research interests are in computational
learning theory and machine learning. My work in
computational learning theory concerns the
development of mathematical tools for designing
optimal
learning
algorithms.
The
general
mathematics involved is mostly computation theory,
topology and game theory. One of my goals is to
apply learning theory to create optimal learning
algorithms for specific applications. A current project
is the automated discovery of conservation laws in
particle physics. I also work on modelling intelligent,
rational and adaptive behaviour in a game-theoretic
framework. This research draws on game theory,
belief revision theory, and computational logic.
Eleni Stroulia
My research interests lie on the intersection of
Software Engineering and Artificial Intelligence.
More specifically, I am interested in all issues
relevant to the problem of complex system design,
system architecture and system reuse and evolution,
and my research methodology is characterized by
the application of Artificial Intelligence techniques to
these Software Engineering problems.
control of object relational database management
systems. My recent work on default reasoning
investigates the relationship between negative
introspection and the expressive power of
autoepistemic logic. I demonstrate that a classical
modal logic augmented with a new introspection
rule is capable of characterizing almost all default
reasoning semantics. My research in the area of
database management systems involves the use of
logic programming with negation as a framework
for modeling nested and multi-level transactions as
well as implementing concurrency control schemas
for object relational database systems.
Osmar Zaïane
My current research interests include knowledge
and resource discovery from large data collections;
specifically, web mining and data mining from
multimedia repositories (i.e. discovery of interesting
patterns from medical images). One current research
project is on the extraction of access patterns and
user behaviour models from web logs of web-based
learning environments. Knowledge visualization
and representation, as well as knowledge querying
also form part of my research focus. We are
implementing an immersive virtual reality
environment for visualization and interaction with
data mining results in a large three-walled
immersive display.
Jia You
My research interest lies in various logical
formalisms that can serve as the basis for a logic
programming
language
and
that
provide
mechanisms for deduction, abduction, and
induction. My latest research efforts have centered
around
nonmonotonic
reasoning
in
logic
programming, its semantics, proof theory,
implementation techniques, and applications.
Li-Yan Yuan
My research interests include logic programming,
artificial intelligence, and database management
systems. My current research activities focus on
knowledge representation, default reasoning,
disjunctive program semantics, and concurrency
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