In this paper, we investigate motor primitive learning with the Natural Actor-Critic approach. The Natural Actor-Critic consists out of actor updates which are achieved using natur...
In this work we show that entropy (H) and mutual information (MI) can be used as methods for extracting spatially localized features for classification purposes. In order to incre...
Liang Wu, Predrag Neskovic, Etienne Reyes, Elena F...
We present a novel learning framework for pipeline models aimed at improving the communication between consecutive stages in a pipeline. Our method exploits the confidence scores ...
Decentralized decision making under uncertainty has been shown to be intractable when each agent has different partial information about the domain. Thus, improving the applicabil...
In many real-world collective decision problems, the set of alternatives is a Cartesian product of finite value domains for each of a given set of variables. The prohibitive size...