In many sensing applications we must continuously gather information to provide a good estimate of the state of the environment at every point in time. A robot may tour an environ...
Alexandra Meliou, Andreas Krause, Carlos Guestrin,...
Recent research has demonstrated the strong performance of hidden Markov models applied to information extraction--the task of populating database slots with corresponding phrases...
The ways in which an agent’s actions affect the world can often be modeled compactly using a set of relational probabilistic planning rules. This paper addresses the problem of ...
Ashwin Deshpande, Brian Milch, Luke S. Zettlemoyer...
This paper considers trajectory planning problems for autonomous robots in information gathering tasks. The objective of the planning is to maximize the information gathered withi...
Cindy Leung, Shoudong Huang, Ngai Ming Kwok, Gamin...
This article investigates fundamental issues in scaling autonomous personal robots towards open-ended sets of everyday manipulation tasks which involve high complexity and vague j...