This paper describes an approach to automatically learn planning operators by observing expert solution traces and to further refine the operators through practice in a learning-b...
This paper shows how universal learning can be achieved with expert advice. To this aim, we specify an experts algorithm with the following characteristics: (a) it uses only feedba...
We describe a new method for learning the conditional probability distribution of a binary-valued variable from labelled training examples. Our proposed Compositional Noisy-Logica...
We present PLIANT, a learning system that supports adaptive assistance in an open calendaring system. PLIANT learns user preferences from the feedback that naturally occurs during...
Melinda T. Gervasio, Michael D. Moffitt, Martha E....
Multiple-instance learning (MIL) is a popular concept among the AI community to support supervised learning applications in situations where only incomplete knowledge is available....