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AAAI
2010
15 years 8 months ago
PUMA: Planning Under Uncertainty with Macro-Actions
Planning in large, partially observable domains is challenging, especially when a long-horizon lookahead is necessary to obtain a good policy. Traditional POMDP planners that plan...
Ruijie He, Emma Brunskill, Nicholas Roy
IJCAI
2003
15 years 8 months ago
A Planning Algorithm for Predictive State Representations
We address the problem of optimally controlling stochastic environments that are partially observable. The standard method for tackling such problems is to define and solve a Part...
Masoumeh T. Izadi, Doina Precup
TARK
1998
Springer
15 years 10 months ago
Simulative Inference About Nonmonotonic Reasoners
If one has attributed certain initial beliefs to an agent, it is sometimes possible to reason about further beliefs the agent must hold by observing what conclusions one's ow...
Aaron N. Kaplan
ICCV
2007
IEEE
16 years 8 months ago
Learning Higher-order Transition Models in Medium-scale Camera Networks
We present a Bayesian framework for learning higherorder transition models in video surveillance networks. Such higher-order models describe object movement between cameras in the...
Ryan Farrell, David S. Doermann, Larry S. Davis
GRC
2010
IEEE
15 years 7 months ago
Learning Multiple Latent Variables with Self-Organizing Maps
Inference of latent variables from complicated data is one important problem in data mining. The high dimensionality and high complexity of real world data often make accurate infe...
Lili Zhang, Erzsébet Merényi