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IJCAI
2007
15 years 3 months ago
Using Linear Programming for Bayesian Exploration in Markov Decision Processes
A key problem in reinforcement learning is finding a good balance between the need to explore the environment and the need to gain rewards by exploiting existing knowledge. Much ...
Pablo Samuel Castro, Doina Precup
ENTCS
2008
119views more  ENTCS 2008»
15 years 1 months ago
An Example of Cloning Graph Transformation Rules for Programming
Graphical notations are already popular for the design of software, as witnessed by the success of the Uniform Modeling Languages (UML). In this paper, we advocate the use of grap...
Mark Minas, Berthold Hoffmann
121
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SARA
2009
Springer
15 years 6 months ago
Rewriting Constraint Models with Metamodels
An important challenge in constraint programming is to rewrite constraint models into executable programs calculating the solutions. This phase of constraint processing may requir...
Raphaël Chenouard, Laurent Granvilliers, Rica...
CCE
2010
14 years 11 months ago
A simple heuristic for reducing the number of scenarios in two-stage stochastic programming
In this work we address the problem of solving multiscenario optimization models that are deterministic equivalents of two-stage stochastic programs. We present a heuristic approx...
Ramkumar Karuppiah, Mariano Martín, Ignacio...
AGP
2010
IEEE
15 years 5 months ago
The Transformational Approach to Program Development
We present an overview of the program transformation techniques which have been proposed over the past twenty-five years in the context of logic programming. We consider the appro...
Alberto Pettorossi, Maurizio Proietti, Valerio Sen...