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» Learning Evaluation Functions for Large Acyclic Domains
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ICML
2006
IEEE
14 years 9 months ago
Fast direct policy evaluation using multiscale analysis of Markov diffusion processes
Policy evaluation is a critical step in the approximate solution of large Markov decision processes (MDPs), typically requiring O(|S|3 ) to directly solve the Bellman system of |S...
Mauro Maggioni, Sridhar Mahadevan
SDM
2012
SIAM
305views Data Mining» more  SDM 2012»
11 years 11 months ago
Learning Hierarchical Relationships among Partially Ordered Objects with Heterogeneous Attributes and Links
Objects linking with many other objects in an information network may imply various semantic relationships. Uncovering such knowledge is essential for role discovery, data cleanin...
Chi Wang, Jiawei Han, Qi Li, Xiang Li, Wen-Pin Lin...
STTT
2008
162views more  STTT 2008»
13 years 8 months ago
Coping with large design spaces: design problem solving in fluidic engineering
Abstract This paper is about tool support for knowledgeintensive engineering tasks. In particular, it introduces software technology to assist the design of complex technical syste...
Benno Stein
AIEDAM
2011
13 years 3 months ago
Discovering implicit constraints in design
In familiar design domains, expert designers are able to quickly focus on “good designs”, based on constraints they have learned while exploring the design space. This ability ...
Madan Mohan Dabbeeru, Amitabha Mukerjee
UAI
2008
13 years 10 months ago
Dyna-Style Planning with Linear Function Approximation and Prioritized Sweeping
We consider the problem of efficiently learning optimal control policies and value functions over large state spaces in an online setting in which estimates must be available afte...
Richard S. Sutton, Csaba Szepesvári, Alborz...