In this paper, we propose a policy gradient reinforcement learning algorithm to address transition-independent Dec-POMDPs. This approach aims at implicitly exploiting the locality...
The generalization of policies in reinforcement learning is a main issue, both from the theoretical model point of view and for their applicability. However, generalizing from a se...
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 ...
In order to produce robots which can interact more effectively with humans we propose that it is necessary for their cognitive processes to be grounded in the same perceptual elem...
We report about a project which brings together Natural Language Processing and eLearning. One of the functionalities developed within this project is the possibility to annotate ...