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ROBOCUP
2007
Springer
153views Robotics» more  ROBOCUP 2007»
14 years 1 months ago
Model-Based Reinforcement Learning in a Complex Domain
Reinforcement learning is a paradigm under which an agent seeks to improve its policy by making learning updates based on the experiences it gathers through interaction with the en...
Shivaram Kalyanakrishnan, Peter Stone, Yaxin Liu
WSC
2008
13 years 10 months ago
A simulator to improve waiting times at a Medical Imaging Center
Medical Imaging Centers (MIC) are critical units in every hospital or medical center because they are an important step in generating a patient's diagnostic. This paper shows...
Francisco J. Ramis, Felipe F. Baesler, Edgar Berho...
IJCV
1998
96views more  IJCV 1998»
13 years 7 months ago
The Intrinsic Structure of Optic Flow Incorporating Measurement Duality
The purpose of this article is to define optic flow for scalar and density images without using a priori knowledge other than its defining conservation principle, and to incorpo...
Luc Florack, Wiro J. Niessen, Mads Nielsen
CMG
2003
13 years 9 months ago
{Performance Modeling and Evaluation of Large-Scale J2EE Applications
The queueing Petri net (QPN) paradigm provides a number of benefits over conventional modeling paradigms such as queueing networks and generalized stochastic Petri nets. Using qu...
Samuel Kounev, Alejandro P. Buchmann
COOPIS
2002
IEEE
14 years 15 days ago
Composing and Deploying Grid Middleware Web Services Using Model Driven Architecture
Rapid advances in networking, hardware, and middleware technologies are facilitating the development and deployment of complex grid applications, such as large-scale distributed co...
Aniruddha S. Gokhale, Balachandran Natarajan