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» Inductive Logic Programming: Derivations, Successes and Shor...
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JSAI
2005
Springer
14 years 26 days ago
Learning Stochastic Logical Automaton
Abstract. This paper is concerned with algorithms for the logical generalisation of probabilistic temporal models from examples. The algorithms combine logic and probabilistic mode...
Hiroaki Watanabe, Stephen Muggleton
ML
2008
ACM
150views Machine Learning» more  ML 2008»
13 years 7 months ago
Learning probabilistic logic models from probabilistic examples
Abstract. We revisit an application developed originally using Inductive Logic Programming (ILP) by replacing the underlying Logic Program (LP) description with Stochastic Logic Pr...
Jianzhong Chen, Stephen Muggleton, José Car...
ILP
2007
Springer
14 years 1 months ago
Relational Macros for Transfer in Reinforcement Learning
We describe an application of inductive logic programming to transfer learning. Transfer learning is the use of knowledge learned in a source task to improve learning in a related ...
Lisa Torrey, Jude W. Shavlik, Trevor Walker, Richa...
CADE
2010
Springer
13 years 8 months ago
Beluga: A Framework for Programming and Reasoning with Deductive Systems (System Description)
Beluga is an environment for programming and reasoning about formal systems given by axioms and inference rules. It implements the logical framework LF for specifying and prototypi...
Brigitte Pientka, Joshua Dunfield
AAAI
2006
13 years 8 months ago
Unifying Logical and Statistical AI
Intelligent agents must be able to handle the complexity and uncertainty of the real world. Logical AI has focused mainly on the former, and statistical AI on the latter. Markov l...
Pedro Domingos, Stanley Kok, Hoifung Poon, Matthew...