While recent research on rule learning has focussed largely on finding highly accurate hypotheses, we evaluate the degree to which these hypotheses are also simple, that is small....
Many learning systems suffer from the utility problem; that is, that time after learning is greater than time before learning. Discovering how to assure that learned knowledge wil...
RVRL (Rule Value Reinforcement Learning) is a new algorithm which extends an existing learning framework that models the environment of a situated agent using a probabilistic rule...