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ICML
2006
IEEE
15 years 9 months ago
Automatic basis function construction for approximate dynamic programming and reinforcement learning
We address the problem of automatically constructing basis functions for linear approximation of the value function of a Markov Decision Process (MDP). Our work builds on results ...
Philipp W. Keller, Shie Mannor, Doina Precup
SAS
2004
Springer
134views Formal Methods» more  SAS 2004»
15 years 8 months ago
Towards Declarative Programming for Web Services
ness Refinement in Abstract Symbolic Trajectory Evaluation . . . . 38 Mila Dalla Preda Constraint-Based Linear-Relations Analysis . . . . . . . . . . . . . . . . . . . . . . . . ....
Sheila A. McIlraith
ENTCS
2006
154views more  ENTCS 2006»
15 years 3 months ago
Quantitative Static Analysis Over Semirings: Analysing Cache Behaviour for Java Card
We present a semantics-based technique for modeling and analysing resource usage behaviour of programs written in a simple object oriented language like Java e code. The approach ...
Pascal Sotin, David Cachera, Thomas P. Jensen
VMCAI
2007
Springer
15 years 9 months ago
Constraint Solving for Interpolation
Interpolation is an important component of recent methods for program verification. It provides a natural and effective means for computing separation between the sets of ‘good...
Andrey Rybalchenko, Viorica Sofronie-Stokkermans
AAAI
2006
15 years 4 months ago
Learning Basis Functions in Hybrid Domains
Markov decision processes (MDPs) with discrete and continuous state and action components can be solved efficiently by hybrid approximate linear programming (HALP). The main idea ...
Branislav Kveton, Milos Hauskrecht