UTCS/AI: Robert Holte/University of Alberta Methods for Predicting IDA*'s Performance ACES 2.302 Tuesday February 19 2008 2:00 p.m.
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Type of Talk: UTCS Colloquium/AI
Date/Time: Tuesday Februar
y 19 2008 2:00 p.m.
Location: ACES 2.302
Host: Bruce Port
er
Talk Title: Methods for Predicting IDA*''s Performance
Ta
lk Abstract:
The goal of the research presented in this talk is to accur
ately predict
the number of nodes that the heuristic search algorithm ID
A* will expand
for a given depth bound heuristic and start state or se
t of start states.
The talk begins by describing the landmark paper by M
ike Reid and
Rich Korf in AAAI 1998. This paper presented a simple but
very effective
analysis framework and developed a formula that was shown
experimentally
to make almost perfect predictions. This prediction met
hod has two
shortcomings (1) it is only applicable when the given heuris
tic is consistent;
(2) its predictions are accurate only for average pe
rformance over a large
random sample of start states. The talk then desc
ribes recent work that
overcomes these two obstacles. The method present
ed makes accurate
predictions for consistent and inconsistent heuristics
and for arbitrary sets of
start states (including individual start stat
es).
Speaker Bio:
Professor Robert Holte is a well-known member o
f the international machine
learning research community former editor-i
n-chief of the leading international
journal in this field (Machine Lear
ning) and current director of the Alberta
Ingenuity Centre for Machine
Learning. His main scientific contributions are his
seminal works on the
problem of small disjuncts and the performance of very
simple classific
ation rules. His current machine learning research investigates
cost-sen
sitive learning and learning in game-playing (for example: opponent
mode
ling in poker and the use of learning for gameplay analysis of commercial
computer games). In addition to machine learning he undertakes
research
in single-agent search (pathfinding): in particular the use of
automati
c abstraction techniques to speed up search. He has over 55 scientific
p
apers to his credit covering both pure and applied research and has serve
d
on the steering committee or program committee of numerous major
in
ternational AI conferences.
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