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» Learning to Optimize Plan Execution in Information Agents
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AAAI
2007
13 years 9 months ago
Nonmyopic Informative Path Planning in Spatio-Temporal Models
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,...
AAAI
2000
13 years 8 months ago
Information Extraction with HMM Structures Learned by Stochastic Optimization
Recent research has demonstrated the strong performance of hidden Markov models applied to information extraction--the task of populating database slots with corresponding phrases...
Dayne Freitag, Andrew McCallum
DAGSTUHL
2007
13 years 9 months ago
Learning Probabilistic Relational Dynamics for Multiple Tasks
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...
RAS
2006
111views more  RAS 2006»
13 years 7 months ago
Planning under uncertainty using model predictive control for information gathering
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...
RAS
2010
164views more  RAS 2010»
13 years 5 months ago
Towards performing everyday manipulation activities
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...
Michael Beetz, Dominik Jain, Lorenz Mösenlech...