Tuesday
Logic is still a fundamental and useful representation for knowledge in Artificial Intelligence. In the area of Machine Learning, various types of computational logic, such as logic programs, first-order logic, description logic, higher-order logic, have developed by incorporating with various types of learning methdologies including identification in the limit, PAC learning, on-line learning, query learning, machine discovery, and learning based on Bayesian networks. On the other hand, machine learning procedures frequently provide semantics to logic and foundations of some procedures in mathematics.
This workshop is proposed to bring together researchers who are interested in both of the areas of machine learning and computational logic, and to have intensive discussions on various relations between the two with making their interchange more active.
Topics
- Learning and knowledge discovery using logics
- Logics (including probablistic logic and stochastic logic) for
machine learning and knowledge discovery
- Logics using machine learning
- Machine learning as a foundation of mathematics/mathematical
procedures
- Learning and knowledge discovery from relational data
- Learning and knowledge discovery from structured/semi-structured
data
- Algorithmic aspects of learning based on logics