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» Learning first-order Markov models for control
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ICRA
1998
IEEE
141views Robotics» more  ICRA 1998»
13 years 11 months ago
On Discontinuous Human Control Strategies
Models of human control strategy (HCS), which accurately emulate dynamic human behavior, have far reaching potential in areas ranging from robotics to virtual reality to the intel...
Michael C. Nechyba, Yangsheng Xu
CORR
2011
Springer
219views Education» more  CORR 2011»
13 years 2 months ago
Active Markov Information-Theoretic Path Planning for Robotic Environmental Sensing
Recent research in multi-robot exploration and mapping has focused on sampling environmental fields, which are typically modeled using the Gaussian process (GP). Existing informa...
Kian Hsiang Low, John M. Dolan, Pradeep K. Khosla
ICML
1997
IEEE
14 years 8 months ago
Predicting Multiprocessor Memory Access Patterns with Learning Models
Machine learning techniques are applicable to computer system optimization. We show that shared memory multiprocessors can successfully utilize machine learning algorithms for mem...
M. F. Sakr, Steven P. Levitan, Donald M. Chiarulli...
ICRA
2008
IEEE
173views Robotics» more  ICRA 2008»
14 years 1 months ago
Bayesian reinforcement learning in continuous POMDPs with application to robot navigation
— We consider the problem of optimal control in continuous and partially observable environments when the parameters of the model are not known exactly. Partially Observable Mark...
Stéphane Ross, Brahim Chaib-draa, Joelle Pi...
EMNLP
2004
13 years 8 months ago
Induction of Greedy Controllers for Deterministic Treebank Parsers
Most statistical parsers have used the grammar induction approach, in which a stochastic grammar is induced from a treebank. An alternative approach is to induce a controller for ...
Tom Kalt