Learning from experimentation allows a system to acquire planning domain knowledge by correcting its knowledge when an action execution fails. Experiments are designed and planned...
position paper. Historically two types of NLP have been investigated: fully automated processing of language by machines (NLP) and autonomous processing of natural language by peop...
In this paper we focus on the adaptation of boosting to grammatical inference. We aim at improving the performances of state merging algorithms in the presence of noisy data by us...
Jean-Christophe Janodet, Richard Nock, Marc Sebban...
Efficient learnability using the state merging algorithm is known for a subclass of probabilistic automata termed µ-distinguishable. In this paper, we prove that state merging alg...
Omri Guttman, S. V. N. Vishwanathan, Robert C. Wil...
We propose a new algorithm for recovering asynchronously from failures in a distributed computation. Our algorithm is based on two novel concepts - a fault-tolerant vector clock t...