2103 search results - page 16 / 421 » Approximate Learning of Dynamic Models |
128
Voted
NIPS
1996
15 years 3 months ago
1996
Dynamic Programming, Q-learning and other discrete Markov Decision Process solvers can be applied to continuous d-dimensional state-spaces by quantizing the state space into an arr...
102
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ICS
2010
Tsinghua U.
15 years 11 months ago
2010
Tsinghua U.
: We study the design of mechanisms in combinatorial auction domains. We focus on settings where the auction is repeated, motivated by auctions for licenses or advertising space. W...
113
Voted
ICML
1995
IEEE
16 years 2 months ago
1995
IEEE
The success ofreinforcement learninginpractical problems depends on the ability to combine function approximation with temporal di erence methods such as value iteration. Experime...
141
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JCP
2007
15 years 1 months ago
2007
Abstract— We describe a general method to transform a non-Markovian sequential decision problem into a supervised learning problem using a K-bestpaths algorithm. We consider an a...
112
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ACL
2007
15 years 3 months ago
2007
We propose a new language learning model that learns a syntactic-semantic grammar from a small number of natural language strings annotated with their semantics, along with basic ...