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SIGECOM
2009
ACM
114views ECommerce» more  SIGECOM 2009»
15 years 6 months ago
Policy teaching through reward function learning
Policy teaching considers a Markov Decision Process setting in which an interested party aims to influence an agent’s decisions by providing limited incentives. In this paper, ...
Haoqi Zhang, David C. Parkes, Yiling Chen
ADHOCNETS
2010
Springer
14 years 8 months ago
DCLA: A Duty-Cycle Learning Algorithm for IEEE 802.15.4 Beacon-Enabled WSNs
The current specification for IEEE 802.15.4 beacon-enabled networks does not define how active and sleep schedules should be configured in order to achieve the optimal network perf...
Rodolfo de Paz Alberola, Dirk Pesch
JMLR
2010
162views more  JMLR 2010»
14 years 6 months ago
A Surrogate Modeling and Adaptive Sampling Toolbox for Computer Based Design
An exceedingly large number of scientific and engineering fields are confronted with the need for computer simulations to study complex, real world phenomena or solve challenging ...
Dirk Gorissen, Ivo Couckuyt, Piet Demeester, Tom D...
JMLR
2008
209views more  JMLR 2008»
14 years 11 months ago
Bayesian Inference and Optimal Design for the Sparse Linear Model
The linear model with sparsity-favouring prior on the coefficients has important applications in many different domains. In machine learning, most methods to date search for maxim...
Matthias W. Seeger
ATAL
2008
Springer
15 years 1 months ago
No-regret learning and a mechanism for distributed multiagent planning
We develop a novel mechanism for coordinated, distributed multiagent planning. We consider problems stated as a collection of single-agent planning problems coupled by common soft...
Jan-P. Calliess, Geoffrey J. Gordon