Policy gradient (PG) reinforcement learning algorithms have strong (local) convergence guarantees, but their learning performance is typically limited by a large variance in the e...
—The subject of this work is the patrolling of an environment with the aid of a team of autonomous agents. We consider both the design of open-loop trajectories with optimal prop...
Fabio Pasqualetti, Antonio Franchi, Francesco Bull...
A prototype system has been designed to automate the extraction of bibliographic data (e.g., article title, authors, , affiliation and others) from online biomedical journals to p...
Competitive analysis is the established tool for measuring the output quality of algorithms that work in an online environment. Recently, the model of advice complexity has been in...
To develop effective learning algorithms for online cursive word recognition is still a challenge research issue. In this paper, we propose a probabilistic framework to model the ...