Domain-specific features are important in representing problem structure throughout machine learning and decision-theoretic planning. In planning, once state features are provide...
— Developing a problem-domain independent methodology to automatically generate high performing solving strategies for specific problems is one of the challenging trends on hype...
Abstract. We compare three systems for the task of synthesising functional recursive programs, namely Adate, an approach through evolutionary computation, the classification learn...
Martin Hofmann 0008, Andreas Hirschberger, Emanuel...
This paper presents an algorithm called IBP that combines case-based and model-based reasoning for an interpretive CBR application, predicting the outcome of legal cases. IBP uses ...
Abstract. This paper introduces Higher-Order Bayesian Networks, a probabilistic reasoning formalism which combines the efficient reasoning mechanisms of Bayesian Networks with the...