Computational Theories of Learning and
Reasoning
Fall 2001
Articles, notes and slides of paper presentations will be available
here. A partial list is available. I will try to have all papers
available on-line.
Download software for viewing ps/gzipped papers
A background task
In order to think in a more concrete way when we read and discuss the
papers we will use a the problem of story comprehension as a
background task. All the presentations and the write-ups will address
this key problem and will evaluate the relevance of the approach
studied with this tasks in mind.
Foundations
Reasoning paradigms (propositional)
Learning to Reason
Expressive Representations
- Presentation #7 (10/16):
(p) Levesque, Brachman:
A fundamental tradeoff in knowledge representation and reasoning.
Presentation by: Chris Neihengen
(r) Woods:
What's in a link.
- Discussion (10/23)
(r) Roth:
Learning to Reason: The Non-Monotonic Case.
- Presentation #8 (10/23):
(p) McAllester, Givan:
Natural Language Syntax and First Order Inference.
Presentation by: Ramya Nagarajan
Expressive Representations; Natural Language
- Presentation #9 (10/25):
(p) Charniak:
Jack and Janet in search of a theory of knowledge.
Presentation by: Arun Bhalla
- Presentation #10 (10/30):
(p) Schubert, Pelletier:
From English to Logic: Context Free Computation of Conventional Logical Translations.
Presentation by: Melissa Poole
- Presentation #11 (11/1):
(p) Moore:
Problems in Logical Forms.
Presentation by: Scott Yih
(r) Moore:
In defense of Logic.
- Presentation #12 (11/6):
(p) Hobbs, Stickel:
Interpretation as Abduction.
Presentation by: Chad Cumby
Probabilistic Representations
- Presentation #13 (11/6), Tuesday afternoon, 5:15,, 2261 DCL.
(p) Pearl:
Fusion, Propagation and Structuring in Belief Networks.
Presentation by: Adam Laud
(r) Roth:
On the hardness of approximate reasoning.
- Presentation #14 (11/8):
(p) Darwiche:
A Differential Approach to Inference in Bayesian Networks.
Presentation by: Xin Li
- Presentation #15 (11/27):
(p) Ngo, Haddawy
Answering queries from context sensitive probabilistic knowledge bases.
Presentation by: Stephen Kloder
(r) Ngo, Haddawy
Probabilistic Logic Programming and Bayesian Networks.
- Presentation #16 (11/27), Tuesday afternoon, 5:15, 2261 DCL:
(p) Kersting, De Raedt
Bayesian Logic Programs.
Presentation by: Howard Sun
- Presentation #17: (11/29)
(p) Koller, Pfeffer:
Probabilistic frame-based systems..
Presentation by: Ira Cohen
(r) Jaeger:
Relational Bayesian networks..
- Presentation #18 (11/29): Thursday afternoon, 5pm, 2261 DCL.
(p) Getoor, Friedman, Koller, Pfeffer:
Learning Probabilistic Relational Models
.
Presentation by: Dav Zimak
Dan Roth