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» Practical Reinforcement Learning in Continuous Spaces
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INFOCOM
2009
IEEE
14 years 3 months ago
An Adaptive Link Layer for Range Diversity in Multi-Radio Mobile Sensor Networks
—An important challenge in mobile sensor networks is to enable energy-efficient communication over a diversity of distances while being robust to wireless effects caused by node...
Jeremy Gummeson, Deepak Ganesan, Mark D. Corner, P...
JMLR
2008
88views more  JMLR 2008»
13 years 8 months ago
Universal Multi-Task Kernels
In this paper we are concerned with reproducing kernel Hilbert spaces HK of functions from an input space into a Hilbert space Y, an environment appropriate for multi-task learnin...
Andrea Caponnetto, Charles A. Micchelli, Massimili...
AAAI
2006
13 years 10 months ago
Hard Constrained Semi-Markov Decision Processes
In multiple criteria Markov Decision Processes (MDP) where multiple costs are incurred at every decision point, current methods solve them by minimising the expected primary cost ...
Wai-Leong Yeow, Chen-Khong Tham, Wai-Choong Wong
NIPS
1998
13 years 10 months ago
A Polygonal Line Algorithm for Constructing Principal Curves
Principal curves have been defined as "self consistent" smooth curves which pass through the "middle" of a d-dimensional probability distribution or data cloud...
Balázs Kégl, Adam Krzyzak, Tam&aacut...
ICML
2010
IEEE
13 years 9 months ago
Inverse Optimal Control with Linearly-Solvable MDPs
We present new algorithms for inverse optimal control (or inverse reinforcement learning, IRL) within the framework of linearlysolvable MDPs (LMDPs). Unlike most prior IRL algorit...
Dvijotham Krishnamurthy, Emanuel Todorov