Logic-Based Artificial Intelligence
CS 395T: Logic-Based Artificial Intelligence, Spring 2011
Course Description
Ideas and methods of mathematical logic have always played an important role
in the theory of knowledge representation. Logic became relevant to AI
research in yet another way when we started using fast satisfiability
solvers for solving combinatorial search problems. In this class we will
spend most of the time studying one of the latest developments in the area
of logic-based AI, answer set programming.
Time and place: TTh 2-3:30,
BUR 224.
Instructor:
Vladimir
Lifschitz
(vl@cs.utexas.edu)
Office hours: T 11-12 and by appointment,
MAI 2010.
TA:
Fangkai Yang
(fkyang@cs.utexas.edu)
Office hours: F 3-4 and by appointment,
MAI 2004.
Prerequisite: Graduate standing.
Grading will be based on class participation.
Online Resources
-
John McCarthy,
What is artificial intelligence?
-
John McCarthy,
Programs with common sense
-
Wikipedia articles on
-
Vladimir Lifschitz, Leora Morgenstern and David Plaisted,
Knowledge representation and classical logic
-
Gerhard Brewka, Ilkka Niemelä and Mirosław Truszczyński,
Nonmonotonic reasoning
- Logical notation in disguise:
-
Wikipedia article on
Prolog
-
Henry Kautz and Bart Selman,
Planning as satisfiability
-
Carla Gomes, Henry Kautz, Ashish Sabharwal and Bart Selman,
Satisfiability solvers
-
Vladimir Lifschitz,
What is answer set programming?
-
Vladimir Lifschitz,
Thirteen definitions of a stable model
-
Michael Gelfond,
Answer sets
-
Martin Gebser, Ronald Kaminski, Benjamin Kaufmann, Max Ostrowski, Torsten
Schaub and Sven Thiele,
User's guide to CLINGO
-
Examples of graphs:
- 2011
Answer Set Programming Competition
- Stuart Shapiro, The Job Puzzle: a challenge
for logical expressibility and automated reasoning
- Raphael Finkel, Victor Marek and Miroslaw Truszczynski,
Constraint Lingo: towards high-level constraint
programming
- Timo Soininen and Ilkka Niemela, Developing a declarative rule language for applications in
product configuration
- Martin Gebser, Ronald Kaminski, Benjamin Kaufmann and Torsten Schaub,
Challenges in answer set solving
- Vladimir Lifschitz,
Answer set programming and plan generation
- Monica Nogueira, Marcello Balduccini, Michael Gelfond, Richard Watson
and Matthew Barry, An A-Prolog decision support system for the Space Shuttle
Handouts