252 search results - page 4 / 51 » Learning Partially Observable Action Models: Efficient Algor... |
109
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ECML
2005
Springer
15 years 5 months ago
2005
Springer
Partially Observable Markov Decision Processes (POMDP) provide a standard framework for sequential decision making in stochastic environments. In this setting, an agent takes actio...
128
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ATAL
2007
Springer
15 years 3 months ago
2007
Springer
Models of agent-environment interaction that use predictive state representations (PSRs) have mainly focused on the case of discrete observations and actions. The theory of discre...
103
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ATAL
2010
Springer
15 years 21 days ago
2010
Springer
A central problem in artificial intelligence is to choose actions to maximize reward in a partially observable, uncertain environment. To do so, we must learn an accurate model of ...
ICML
2009
IEEE
16 years 12 days ago
2009
IEEE
Large margin learning of Continuous Density HMMs with a partially labeled dataset has been extensively studied in the speech and handwriting recognition fields. Yet due to the non...
121
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AAAI
2012
13 years 2 months ago
2012
We present the first real-world benchmark for sequentiallyoptimal team formation, working within the framework of a class of online football prediction games known as Fantasy Foo...