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» Learning Stochastic Logic Programs
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FLAIRS
1998
13 years 9 months ago
Optimizing Production Manufacturing Using Reinforcement Learning
Manyindustrial processes involve makingparts with an assemblyof machines, where each machinecarries out an operation on a part, and the finished product requires a wholeseries of ...
Sridhar Mahadevan, Georgios Theocharous
JMLR
2012
11 years 10 months ago
PAC-Bayes-Bernstein Inequality for Martingales and its Application to Multiarmed Bandits
We develop a new tool for data-dependent analysis of the exploration-exploitation trade-off in learning under limited feedback. Our tool is based on two main ingredients. The fi...
Yevgeny Seldin, Nicolò Cesa-Bianchi, Peter ...
JMLR
2010
111views more  JMLR 2010»
13 years 2 months ago
An EM Algorithm on BDDs with Order Encoding for Logic-based Probabilistic Models
Logic-based probabilistic models (LBPMs) enable us to handle problems with uncertainty succinctly thanks to the expressive power of logic. However, most of LBPMs have restrictions...
Masakazu Ishihata, Yoshitaka Kameya, Taisuke Sato,...
CP
2004
Springer
14 years 1 months ago
Decomposition and Learning for a Hard Real Time Task Allocation Problem
Abstract. We present a cooperation technique using an accurate management of nogoods to solve a hard real-time problem which consists in assigning periodic tasks to processors in t...
Hadrien Cambazard, Pierre-Emmanuel Hladik, Anne-Ma...
IEAAIE
2004
Springer
14 years 1 months ago
An Algorithm for Incremental Mode Induction
Learning systems have been devised as a way of overcoming the knowledge acquisition bottleneck in the development of knowledge-based systems. They often cast learning to a search p...
Nicola Di Mauro, Floriana Esposito, Stefano Ferill...