CPSC 522 - Artificial Intelligence 2
Schedule
Spring 2018
Here is a tentative schedule. The dates for all topics in the
future should be regarded as fiction. Which students are presenting on
each day: http://wiki.ubc.ca/Course:CPSC522/StudentPresentations2018.
- Jan 4 - AI and Agents. Slides: lect1.pdf, lect2.pdf. Readings:
AIFCA 2e: chapter 1.
- Jan 9 - Graphical models (big picture). Slides:
lect1.pdf,
lect2.pdf.
Readings:
AIFCA 2e: Sections 8.1-8.3.
- Jan 11 - Graphical models (inference and learning). Readings:
AIFCA 2e: Sections 8.4, 10.1, 10.3,
10.4.
- Jan 16 - Conditional
independence and Local structure. (was: Student presentations:
-
Mark Chavira and Adnan
Darwiche, On probabilistic inference by weighted model counting
Artificial Intelligence
Volume 172, Issues 6-7, April 2008
-
Probabilistic inference in hybrid domains by weighted model integration.
V Belle, A Passerini, G Van den Broeck. Proceedings IJCAI 2015
- Jan 18 - Learning probabilistic models. lect1, lect3, lect4
- Jan 23 - causality. time .
(was Student presentations:
-
Monte Carlo Localization: Efficient Position Estimation for Mobile Robots
D. Fox, Burgard, W., Dellaert, F., Thrun, S., AAAI, 1999
-
FastSLAM: A factored solution to the simultaneous localization and mapping problem
M Montemerlo, S Thrun, D Koller, B Wegbreit - Aaai/iaai, 2002
- Jan 25 - Uncertainty and time.
- Jan 30 - Preferences and utility. (Was Student presentations:
-
Bareinboim, E., and Pearl, J. 2016. Causal inference and the
data-fusion problem. Proceedings of the National Academy of Sciences
113(27):7345-7352.
-
Shpitser, I., K. Mohan, and J. Pearl (2015). Missing data as a causal and probabilistic
problem. In
Proceedings of the Thirty-First Conference on Uncertainty in Artificial
Intelligence
- Feb 1 - Actions,
uncertainty and utility. Valuecharts
- Feb 6 - Guest lecture: Mehran Kazemi on knowledge-base completion
- Feb 8 - Student presentations:
-
Simultaneous Elicitation of Preference Features and Utility.
Craig Boutilier, Kevin Regan and Paolo Viappiani.
Proceedings of the Twenty-fourth AAAI Conference on Artificial Intelligence (AAAI-10) , pp.1160--1167, Atlanta GA (2010).
-
Adapting a Kidney Exchange Algorithm to Align with Human Values
Rachel Freedman,
Jana Schaich Borg, Walter Sinnott-Armstrong
John P. Dickerson
Vincent Conitzer, Proc. AAAI-2018.
https://users.cs.duke.edu/~conitzer/kidneyAAAI18.pdf.
- Feb 13 - Goal-oriented planning
- Feb 15 - Student presentations:
-
Muise, C.; McIlraith, S. A.; and Beck, J. C. 2012. Improved
Non-deterministic Planning by Exploiting State Relevance. In Proc. of
the 22th International Conference on Automated Planning and Scheduling (ICAPS)
, 172-180
-
Best-First Width Search: Exploration and Exploitation in Classical
Planning. N Lipovetzky, H Geffner. Proc. AAAI 2017
- Feb 27 - Decision-theoretic
planning, reinforcement
learning. value
iteration app.
- Mar 1 - Student presentations:
-
Kocsis, L., and Szepesvari, C. 2006. Bandit Based Monte-Carlo Planning. In
Proceedings of the 17th European Conference on Machine Learning (ECML), 282-293.
-
Keller, T., and Eyerich, P. 2012. PROST: Probabilistic Planning
Based on UCT
- Mar 6 - Reinforcement Learning
- Mar 8 - Student presentations:
- Mar 13 - Multi-agent systems
- Mar 15 - Student presentations:
-
Temporal Action-Graph Games: A New Representation for Dynamic
Games. A.X. Jiang, K. Leyton-Brown, A. Pfeffer. Uncertainty in
Artificial Intelligence (UAI), pp. 268-276, 2009.
-
Towards a Science of Security Games Thanh H. Nguyen, Debarun Kar, Matthew Brown, Arunesh Sinha, Albert Xin Jiang, Milind Tambe New Frontiers of Multidisciplinary Research in STEAM-H (Book chapter) (edited by B Toni) 2016
http://teamcore.usc.edu/projects/security/
- Mar 20 - Relational models
- Mar 22 - Student presentations:
-
Koren, Y., Bell, R. and Volinsky, C., Matrix Factorization
Techniques for Recommender Systems, IEEE Computer 2009.
-
Translating Embeddings for Modeling
Multi-relational Data,
Antoine Bordes, Nicolas Usunier, Alberto Garcia-Duran,
Jason Weston, Oksana Yakhnenko, NIPS 2013.
- Mar 27 - Probabilisitic programming
- Mar 29 - Student presentations:
-
ProbLog: A probabilistic Prolog and its application in link discovery,
L. De Raedt, A. Kimmig, and H. Toivonen, Proceedings of the 20th
International Joint Conference on Artificial Intelligence (IJCAI-07),
Hyderabad, India, pages 2462-2467, 2007.
https://dtai.cs.kuleuven.be/problog/
-
Wood, F., van de Meent, J. W., & Mansinghka, V. (2015). A New Approach
to Probabilistic Programming Inference.
- April 3 - Student presentations:
-
B. Milch, B. Marthi, S. Russell, D. Sontag, D. L. Ong, and
A. Kolobov. BLOG: Probabilistic models with unknown objects, IJCAI 2005
-
S. H. Bach, B. Huang, B. London, and L. Getoor. Hinge-loss Markov random fields: Convex
inference for structured prediction. In
Uncertainty in Artificial Intelligence (UAI)
, 2013. http://psl.linqs.org/
- Apr 5 - Where to now?
- Mid April - Project presentations
Last updated: 2018-01-08, David Poole