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Constraint Learning and Dynamic Probabilistic Programming
Department of Computer Science, KU Leuven, Leuven, Belgium.ORCID iD: 0000-0002-6860-6303
2017 (English)In: Formal methods and machine learning, 2017Conference paper, Oral presentation with published abstract (Refereed)
Abstract [en]

The talk focussed on two issues. The first was the synthesis of a set of constraints that hold in tabular data (say a set of excel tables). The second was concerned with the use of hybrid probabilistic programs in dynamic domains and its applications in simple robotics and planning settings.

More details on our probabilistic programming language Problog can be found at https://dtai.cs.kuleuven.be/problog/.

Place, publisher, year, edition, pages
2017.
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:oru:diva-96081OAI: oai:DiVA.org:oru-96081DiVA, id: diva2:1621647
Conference
Formal Methods and Machine Learning Seminar, Dagstuhl Seminar 17351, Wadern, Germany, August 27-September 1, 2017
Available from: 2021-12-20 Created: 2021-12-20 Last updated: 2021-12-21Bibliographically approved

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De Raedt, Luc

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CiteExportLink to record
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Citation style
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