Software
Symbolic Perseus
- Author: Pascal Poupart
- Symbolic Perseus is a point-based value iteration algorithm that
uses Algebraic
Decision Diagrams (ADDs) as the underlying data structure to tackle
large factored POMDPs. The original Perseus
algorithm is a point-based value iteration algorithm developed by
Matthijs Spaan and Nikos Vlassis for flat POMDPs.
- Download the code
(written in Matlab and Java):
- POMDP problems
- To be notified about releases, send me an email (ppoupart [at] cs
[dot] uwaterloo [dot] ca). If you find a bug or have
comments/suggestions to improve the code, please do not hesitate to
contact me.
- The best reference for symbolic Perseus is Chapter 5 of my PhD
thesis:
- Exploiting Structure to Efficiently Solve
Large
Scale Partially Observable Markov Decision Processes
Pascal Poupart
Ph.D. thesis, Department of Computer Science, University of Toronto,
Toronto,
2005
[thesis ps] [thesis
ps.gz] [thesis pdf]
- Symbolic Perseus has been used to solve factored POMDPs with up
to 50 million states in the following papers:
- Automated Handwashing
Assistance
for Persons with Dementia Using Video and a Partially Observable Markov
Decision Process
Jesse Hoey, Pascal Poupart, Axel von Bertoldi, Tamy Craig, Craig
Boutilier and Alex Mihailidis
Computer Vision and Image
Understanding (CVIU), accepted January 2009.
[paper.pdf]
- Assisting Persons with
Dementia
during Handwashing Using a Partially Observable Markov Decision Process
Jesse Hoey, Axel von Bertoldi, Pascal Poupart, and Alex Mihailidis
In Proceedings of the
International Conference on Vision Systems (ICVS), Biefeld,
Germany, 2007.
[paper.pdf]
winner of
the best
paper award
- A Decision-Theoretic Approach to Task Assistance for
Persons
with
Dementia
Jennifer Boger, Pascal Poupart, Jesse Hoey, Craig Boutilier, Geoff
Fernie,
and Alex
Mihailidis
In Proceedings of the International Joint Conference on Artificial
Intelligence (IJCAI), pages 1293-1299, Edinburgh, Scotland, 2005
[paper ps]
[paper
ps.gz] [paper
pdf]