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ICML
2004
IEEE
14 years 10 months ago
Learning and discovery of predictive state representations in dynamical systems with reset
Predictive state representations (PSRs) are a recently proposed way of modeling controlled dynamical systems. PSR-based models use predictions of observable outcomes of tests that...
Michael R. James, Satinder P. Singh
PKDD
2007
Springer
193views Data Mining» more  PKDD 2007»
14 years 4 months ago
Learning Multi-dimensional Functions: Gas Turbine Engine Modeling
Abstract. This paper shows how multi-dimensional functions, describing the operation of complex equipment, can be learned. The functions are points in a shape space, each produced ...
Chris Drummond
ICWL
2007
Springer
14 years 4 months ago
Language-Driven Development of Web-Based Learning Applications
In this paper we propose a language-driven approach for the high-level design of web-based learning applications. In our approach we define a domainspecific language that character...
José Luis Sierra, Baltasar Fernández...
COR
2008
142views more  COR 2008»
13 years 10 months ago
Application of reinforcement learning to the game of Othello
Operations research and management science are often confronted with sequential decision making problems with large state spaces. Standard methods that are used for solving such c...
Nees Jan van Eck, Michiel C. van Wezel
ICML
2006
IEEE
14 years 10 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