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FLAIRS
1998
13 years 10 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
NIPS
1998
13 years 10 months ago
Scheduling Straight-Line Code Using Reinforcement Learning and Rollouts
The execution order of a block of computer instructions can make a difference in its running time by a factor of two or more. In order to achieve the best possible speed, compiler...
Amy McGovern, J. Eliot B. Moss
JAIR
2002
99views more  JAIR 2002»
13 years 8 months ago
Optimizing Dialogue Management with Reinforcement Learning: Experiments with the NJFun System
Designing the dialogue policy of a spoken dialogue system involves many nontrivial choices. This paper presents a reinforcement learning approach for automatically optimizing a di...
Satinder P. Singh, Diane J. Litman, Michael J. Kea...
INLG
2010
Springer
13 years 6 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

Publication
151views
12 years 7 months ago
Robust Bayesian reinforcement learning through tight lower bounds
In the Bayesian approach to sequential decision making, exact calculation of the (subjective) utility is intractable. This extends to most special cases of interest, such as reinfo...
Christos Dimitrakakis