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IJCAI
2003
13 years 10 months ago
A Planning Algorithm for Predictive State Representations
We address the problem of optimally controlling stochastic environments that are partially observable. The standard method for tackling such problems is to define and solve a Part...
Masoumeh T. Izadi, Doina Precup
IROS
2006
IEEE
168views Robotics» more  IROS 2006»
14 years 2 months ago
Scanning the Environment with Two Independent Cameras - Biologically Motivated Approach
— In this paper we present a novel method for visual scanning and target tracking by means of independent pan-tilt cameras which mimic the chameleon visual system. We present a s...
Ofir Avni, Francesco Borrelli, Gadi Katzir, Ehud R...
GECCO
2003
Springer
112views Optimization» more  GECCO 2003»
14 years 1 months ago
Dispersion-Based Population Initialization
Reliable execution and analysis of an evolutionary algorithm (EA) normally requires many runs to provide reasonable assurance that stochastic effects have been properly considered...
Ronald W. Morrison
CDC
2010
IEEE
105views Control Systems» more  CDC 2010»
13 years 3 months ago
Universal scheduling for networks with arbitrary traffic, channels, and mobility
We extend stochastic network optimization theory to treat networks with arbitrary sample paths for arrivals, channels, and mobility. The network can experience unexpected link or n...
Michael J. Neely
JAIR
2008
145views more  JAIR 2008»
13 years 8 months ago
Communication-Based Decomposition Mechanisms for Decentralized MDPs
Multi-agent planning in stochastic environments can be framed formally as a decentralized Markov decision problem. Many real-life distributed problems that arise in manufacturing,...
Claudia V. Goldman, Shlomo Zilberstein