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GECCO
2007
Springer
182views Optimization» more  GECCO 2007»
14 years 1 months ago
Stochastic training of a biologically plausible spino-neuromuscular system model
A primary goal of evolutionary robotics is to create systems that are as robust and adaptive as the human body. Moving toward this goal often involves training control systems tha...
Stanley Phillips Gotshall, Terence Soule
AAAI
2008
13 years 11 months ago
Towards Faster Planning with Continuous Resources in Stochastic Domains
Agents often have to construct plans that obey resource limits for continuous resources whose consumption can only be characterized by probability distributions. While Markov Deci...
Janusz Marecki, Milind Tambe
AIPS
2008
13 years 11 months ago
Multiagent Planning Under Uncertainty with Stochastic Communication Delays
We consider the problem of cooperative multiagent planning under uncertainty, formalized as a decentralized partially observable Markov decision process (Dec-POMDP). Unfortunately...
Matthijs T. J. Spaan, Frans A. Oliehoek, Nikos A. ...
JAIR
2008
107views more  JAIR 2008»
13 years 9 months ago
Planning with Durative Actions in Stochastic Domains
Probabilistic planning problems are typically modeled as a Markov Decision Process (MDP). MDPs, while an otherwise expressive model, allow only for sequential, non-durative action...
Mausam, Daniel S. Weld
SIAMCO
2000
71views more  SIAMCO 2000»
13 years 9 months ago
On a Perturbation Approach for the Analysis of Stochastic Tracking Algorithms
In this paper, a perturbation expansion technique is introduced to decompose the tracking error of a general adaptive tracking algorithm in a linear regression model. This method ...
Rafik Aguech, Eric Moulines, Pierre Priouret