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ICRA
2007
IEEE
126views Robotics» more  ICRA 2007»
15 years 4 months ago
A formal framework for robot learning and control under model uncertainty
— While the Partially Observable Markov Decision Process (POMDP) provides a formal framework for the problem of robot control under uncertainty, it typically assumes a known and ...
Robin Jaulmes, Joelle Pineau, Doina Precup
TON
2010
279views more  TON 2010»
14 years 8 months ago
Distributed algorithms for minimum cost multicast with network coding
— We adopt the network coding approach to achieve minimum-cost multicast in interference-limited wireless networks where link capacities are functions of the signal-to-noise-plus...
Yufang Xi, Edmund M. Yeh
ICML
2001
IEEE
15 years 10 months ago
Symmetry in Markov Decision Processes and its Implications for Single Agent and Multiagent Learning
This paper examines the notion of symmetry in Markov decision processes (MDPs). We define symmetry for an MDP and show how it can be exploited for more effective learning in singl...
Martin Zinkevich, Tucker R. Balch
ESANN
2007
14 years 11 months ago
The Recurrent Control Neural Network
This paper presents our Recurrent Control Neural Network (RCNN), which is a model-based approach for a data-efficient modelling and control of reinforcement learning problems in di...
Anton Maximilian Schäfer, Steffen Udluft, Han...
PR
2008
85views more  PR 2008»
14 years 9 months ago
Quadratic boosting
This paper presents a strategy to improve the AdaBoost algorithm with a quadratic combination of base classifiers. We observe that learning this combination is necessary to get be...
Thang V. Pham, Arnold W. M. Smeulders