Workshop on Logic and Learning
Affiliated with LICS 2001
June 19-20, 2001, Boston, Massachusetts

Logic has been used as the underlying representation language in many areas of AI including machine learning. Learnability of logical expressions has been studied in many paradigms including PAC learning, query based learning, inductive inference, and inductive logic programming. There are theoretical results on learning in propositional logic as well as for logic programs, description logic, and fragments of first-order logic. The techniques applied are probabilistic and combinatorial, recursion theoretic, proof theoretic, and model theoretic.

The workshop aims to focus on such logic-based results and techniques for learning, fostering further understanding of the use of logic in learning. The workshop has a two-fold objective: to provide an introduction to the area for those who work in other LICS areas and are interested in applying logic to learning, and to provide a forum for research in the area of logic learning.

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