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INLG
2010
Springer
15 years 1 months ago
Hierarchical Reinforcement Learning for Adaptive Text Generation
We present a novel approach to natural language generation (NLG) that applies hierarchical reinforcement learning to text generation in the wayfinding domain. Our approach aims to...
Nina Dethlefs, Heriberto Cuayáhuitl
123
Voted
JMLR
2010
125views more  JMLR 2010»
14 years 10 months ago
Variational methods for Reinforcement Learning
We consider reinforcement learning as solving a Markov decision process with unknown transition distribution. Based on interaction with the environment, an estimate of the transit...
Thomas Furmston, David Barber
INFOCOM
2008
IEEE
15 years 10 months ago
Opportunistic Scheduling with Reliability Guarantees in Cognitive Radio Networks
—We develop opportunistic scheduling policies for cognitive radio networks that maximize the throughput utility of the secondary (unlicensed) users subject to maximum collision c...
Rahul Urgaonkar, Michael J. Neely
108
Voted
SASO
2007
IEEE
15 years 10 months ago
Shruti: A Self-Tuning Hierarchical Aggregation System
Current aggregation systems either have a single inbuilt aggregation mechanism or require applications to specify an aggregation policy a priori. It is hard to predict the read an...
Praveen Yalagandula, Michael Dahlin
GECCO
2004
Springer
15 years 9 months ago
Modeling Selection Intensity for Toroidal Cellular Evolutionary Algorithms
We present quantitative models for the selection pressure of cellular evolutionary algorithms structured in two dimensional regular lattices. We derive models based on probabilisti...
Mario Giacobini, Enrique Alba, Andrea Tettamanzi, ...