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» Learning to Optimize Plan Execution in Information Agents
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Publication
233views
12 years 7 months ago
Sparse reward processes
We introduce a class of learning problems where the agent is presented with a series of tasks. Intuitively, if there is relation among those tasks, then the information gained duri...
Christos Dimitrakakis
GIS
2006
ACM
14 years 9 months ago
Optimization of multiple continuous queries over streaming satellite data
Remotely sensed data, in particular satellite imagery, play many important roles in environmental applications and models. In particular applications that study (rapid) changes in...
Quinn Hart, Michael Gertz
WSC
2001
13 years 10 months ago
Distributed simulation with incorporated APS procedures for high-fidelity supply chain optimization
Tactical and operational planning for manufacturing enterprises are more important today than ever before as their supply chains span the globe. Two state-of-the-art technologies ...
Peter Lendermann, Boon-Ping Gan, Leon F. McGinnis
HICSS
2003
IEEE
207views Biometrics» more  HICSS 2003»
14 years 2 months ago
Formalizing Multi-Agent POMDP's in the context of network routing
This paper uses partially observable Markov decision processes (POMDP’s) as a basic framework for MultiAgent planning. We distinguish three perspectives: first one is that of a...
Bharaneedharan Rathnasabapathy, Piotr J. Gmytrasie...
VLDB
2005
ACM
126views Database» more  VLDB 2005»
14 years 2 months ago
Consistently Estimating the Selectivity of Conjuncts of Predicates
Cost-based query optimizers need to estimate the selectivity of conjunctive predicates when comparing alternative query execution plans. To this end, advanced optimizers use multi...
Volker Markl, Nimrod Megiddo, Marcel Kutsch, Tam M...