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Hochschulschrift

Using Neural Networks for Distance Estimation in Planning

MPG-Autoren
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Hoffmann,  Jörg
Programming Logics, MPI for Informatics, Max Planck Society;

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Fritz,  Mario
Computer Vision and Multimodal Computing, MPI for Informatics, Max Planck Society;

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Zitation

Ferber, P. (2017). Using Neural Networks for Distance Estimation in Planning. Master Thesis, Universität des Saarlandes, Saarbrücken.


Zitierlink: http://hdl.handle.net/21.11116/0000-0000-3590-1
Zusammenfassung
Abstract We show the applicability of neural networks for distance estimation in classical search problems. First, we present and evaluate different techniques which are able to sample training data from difficult problems of arbitrary domains. Afterwards, an empirical investigation on good neural network configurations for learning a goal dependent heuristic is performed. Finally, the trained networks are evaluated as heuristics in actual searches and compared to state of the art techniques. We have observed that for difficult problems the neural networks perform faster searches and generate better plans than other state of the art techniques.