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Senka Krivic, Michael Cashmore, Bram Ridder, D. Magazzeni, S. Szedmák, J. Piater
1 5. 2. 2017.

Initial State Prediction in Planning

While recent advances in offline reasoning techniques and online execution strategies have made planning under uncertainty more robust, the application of plans in partially-known environments is still a difficult and important topic. In this paper we present an approach for predicting new information about a partially-known initial state, represented as a multi- graph utilizing Maximum-Margin Multi-Valued Regression. We evaluate this approach in four different domains, demonstrating high recall and accuracy.


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