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ASIAN
2004
Springer
107views Algorithms» more  ASIAN 2004»
13 years 10 months ago
A Framework for Compiler Driven Design Space Exploration for Embedded System Customization
Designing custom solutions has been central to meeting a range of stringent and specialized needs of embedded computing, along such dimensions as physical size, power consumption, ...
Krishna V. Palem, Lakshmi N. Chakrapani, Sudhakar ...
COLT
2008
Springer
13 years 6 months ago
Adaptive Aggregation for Reinforcement Learning with Efficient Exploration: Deterministic Domains
We propose a model-based learning algorithm, the Adaptive Aggregation Algorithm (AAA), that aims to solve the online, continuous state space reinforcement learning problem in a de...
Andrey Bernstein, Nahum Shimkin
KBSE
2009
IEEE
13 years 11 months ago
A Framework for State-Space Exploration of Java-Based Actor Programs
—The actor programming model offers a promising model for developing reliable parallel and distributed code. Actors provide flexibility and scalability: local execution may be i...
Steven Lauterburg, Mirco Dotta, Darko Marinov, Gul...
SDM
2009
SIAM
217views Data Mining» more  SDM 2009»
14 years 2 months ago
A Framework for Exploring Categorical Data.
In this paper, we present a framework for categorical data analysis which allows such data sets to be explored using a rich set of techniques that are only applicable to continuou...
Shyam Boriah, Varun Chandola, Vipin Kumar
ECML
2007
Springer
13 years 8 months ago
Efficient Continuous-Time Reinforcement Learning with Adaptive State Graphs
Abstract. We present a new reinforcement learning approach for deterministic continuous control problems in environments with unknown, arbitrary reward functions. The difficulty of...
Gerhard Neumann, Michael Pfeiffer, Wolfgang Maass