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ICMLA
2010
13 years 7 months ago
Incremental Learning of Relational Action Rules
Abstract--In the Relational Reinforcement learning framework, we propose an algorithm that learns an action model allowing to predict the resulting state of each action in any give...
Christophe Rodrigues, Pierre Gérard, C&eacu...
NIPS
2008
13 years 12 months ago
An interior-point stochastic approximation method and an L1-regularized delta rule
The stochastic approximation method is behind the solution to many important, actively-studied problems in machine learning. Despite its farreaching application, there is almost n...
Peter Carbonetto, Mark Schmidt, Nando de Freitas
CORR
2011
Springer
140views Education» more  CORR 2011»
13 years 2 months ago
A Wiki for Business Rules in Open Vocabulary, Executable English
The problem of business-IT alignment is of widespread economic concern. As one way of addressing the problem, this paper describes an online system that functions as a kind of Wik...
Adrian Walker
DIGRA
2005
Springer
14 years 4 months ago
Law, order and conflicts of interest in massively multiplayer online games
In huge online games where great numbers of players can be connected at the same time, social interaction is complex and conflicts become part of everyday life. There is a set of ...
Daniel Pargman, Andreas Eriksson
CORR
2006
Springer
96views Education» more  CORR 2006»
13 years 10 months ago
Metric entropy in competitive on-line prediction
Competitive on-line prediction (also known as universal prediction of individual sequences) is a strand of learning theory avoiding making any stochastic assumptions about the way...
Vladimir Vovk