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NIPS
1996
15 years 7 months ago
Multidimensional Triangulation and Interpolation for Reinforcement Learning
Dynamic Programming, Q-learning and other discrete Markov Decision Process solvers can be applied to continuous d-dimensional state-spaces by quantizing the state space into an arr...
Scott Davies
JSAC
2010
107views more  JSAC 2010»
15 years 4 months ago
Online learning in autonomic multi-hop wireless networks for transmitting mission-critical applications
Abstract—In this paper, we study how to optimize the transmission decisions of nodes aimed at supporting mission-critical applications, such as surveillance, security monitoring,...
Hsien-Po Shiang, Mihaela van der Schaar
NECO
2010
154views more  NECO 2010»
15 years 4 months ago
Role of Homeostasis in Learning Sparse Representations
Neurons in the input layer of primary visual cortex in primates develop edge-like receptive fields. One approach to understanding the emergence of this response is to state that ...
Laurent U. Perrinet
AAMAS
2011
Springer
15 years 1 months ago
Using focal point learning to improve human-machine tacit coordination
We consider an automated agent that needs to coordinate with a human partner when communication between them is not possible or is undesirable (tacit coordination games). Specifi...
Inon Zuckerman, Sarit Kraus, Jeffrey S. Rosenschei...
IEEEPACT
2008
IEEE
16 years 21 days ago
Feature selection and policy optimization for distributed instruction placement using reinforcement learning
Communication overheads are one of the fundamental challenges in a multiprocessor system. As the number of processors on a chip increases, communication overheads and the distribu...
Katherine E. Coons, Behnam Robatmili, Matthew E. T...