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» On Learning with Integral Operators
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AAAI
2012
13 years 9 months ago
Kernel-Based Reinforcement Learning on Representative States
Markov decision processes (MDPs) are an established framework for solving sequential decision-making problems under uncertainty. In this work, we propose a new method for batchmod...
Branislav Kveton, Georgios Theocharous
CDC
2008
IEEE
110views Control Systems» more  CDC 2008»
16 years 1 months ago
Local mode dependent decentralized control of uncertain Markovian jump large-scale systems
Abstract— This paper is concerned with the robust stabilization of a class of stochastic large-scale systems. The uncertainties satisfy integral quadratic constraints. The random...
Junlin Xiong, Valery A. Ugrinovskii, Ian R. Peters...
SRDS
2008
IEEE
16 years 1 months ago
Application-Level Recovery Mechanisms for Context-Aware Pervasive Computing
We identify here various kinds of failure conditions and robustness issues that arise in context-aware pervasive computing applications. Such conditions are related to failures in...
Devdatta Kulkarni, Anand Tripathi
ICES
2003
Springer
165views Hardware» more  ICES 2003»
15 years 12 months ago
Speeding up Hardware Evolution: A Coprocessor for Evolutionary Algorithms
This paper proposes a coprocessor architecture to speed up hardware evolution. It is designed to be implemented in an FPGA with an integrated microprocessor core. The coprocessor r...
Tillmann Schmitz, Steffen G. Hohmann, Karlheinz Me...
DATE
2002
IEEE
151views Hardware» more  DATE 2002»
15 years 11 months ago
Analog Circuit Sizing Using Adaptive Worst-Case Parameter Sets
In this paper, a method for nominal design of analog integrated circuits is presented that includes process variations and operating ranges by worst-case parameter sets. These set...
Robert Schwencker, Frank Schenkel, Michael Pronath...