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» Combining Simple Models to Approximate Complex Dynamics
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PKDD
2009
Springer
144views Data Mining» more  PKDD 2009»
14 years 2 months ago
Compositional Models for Reinforcement Learning
Abstract. Innovations such as optimistic exploration, function approximation, and hierarchical decomposition have helped scale reinforcement learning to more complex environments, ...
Nicholas K. Jong, Peter Stone
GRID
2003
Springer
14 years 26 days ago
Scoped and Approximate Queries in a Relational Grid Information Service
We are developing a grid information service, RGIS, that is based on the relational data model. RGIS supports complex queries written in SQL that search for compositions (using jo...
Dong Lu, Peter A. Dinda, Jason A. Skicewicz
JAIR
2000
152views more  JAIR 2000»
13 years 7 months ago
Value-Function Approximations for Partially Observable Markov Decision Processes
Partially observable Markov decision processes (POMDPs) provide an elegant mathematical framework for modeling complex decision and planning problems in stochastic domains in whic...
Milos Hauskrecht
STOC
2005
ACM
142views Algorithms» more  STOC 2005»
14 years 8 months ago
Market equilibrium via the excess demand function
We consider the problem of computing market equilibria and show three results. (i) For exchange economies satisfying weak gross substitutability we analyze a simple discrete versi...
Bruno Codenotti, Benton McCune, Kasturi R. Varadar...
CEC
2007
IEEE
13 years 9 months ago
Multi-population approach to approximate the development of neocortical networks
— Cultured natural cortical neurons form functional networks through a complex set of developmental steps during the first weeks in vitro. The dynamic behavior of the network in...
Andreas Herzog, Karsten Kube, Bernd Michaelis, Ana...