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Documents authored by Cropper, Andrew

Document
DOI: 10.4230/DagRep.11.4.20
Approaches and Applications of Inductive Programming (Dagstuhl Seminar 21192)

Authors: Andrew Cropper, Luc De Raedt, Richard Evans, and Ute Schmid

Published in: Dagstuhl Reports, Volume 11, Issue 4 (2021)

Abstract
In this report the program and the outcomes of Dagstuhl Seminar 21192 "Approaches and Applications of Inductive Programming" is documented. The goal of inductive programming (IP) is to induce computer programs from data, typically input/output examples of a desired program. IP interests researchers from many areas of computer science, including machine learning, automated reasoning, program verification, and software engineering. Furthermore, IP contributes to research outside computer science, notably in cognitive science, where IP can help build models of human inductive learning and contribute methods for intelligent tutor systems. Building on the success of previous IP Dagstuhl seminars (13502, 15442, 17382, and 19202), the goal of this new edition of the seminar is to focus on IP methods which integrate learning and reasoning, scaling up IP methods to be applicable to more complex real world problems, and to further explore the potential of IP for explainable artificial intelligence (XAI), especially for interactive learning. The extended abstracts included in this report show recent advances in IP research. The included short report of the outcome of the discussion sessions additionally point out interesting interrelation between different aspects and possible new directions for IP.
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Andrew Cropper, Luc De Raedt, Richard Evans, and Ute Schmid. Approaches and Applications of Inductive Programming (Dagstuhl Seminar 21192). In Dagstuhl Reports, Volume 11, Issue 4, pp. 20-33, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@Article{cropper_et_al:DagRep.11.4.20,
  author =	{Cropper, Andrew and De Raedt, Luc and Evans, Richard and Schmid, Ute},
  title =	{{Approaches and Applications of Inductive Programming (Dagstuhl Seminar 21192)}},
  pages =	{20--33},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2021},
  volume =	{11},
  number =	{4},
  editor =	{Cropper, Andrew and De Raedt, Luc and Evans, Richard and Schmid, Ute},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.11.4.20},
  URN =		{urn:nbn:de:0030-drops-147975},
  doi =		{10.4230/DagRep.11.4.20},
  annote =	{Keywords: Interpretable Machine Learning, Explainable Artificial Intelligence, Interactive Learning, Human-like Computing, Inductive Logic Programming}
}
Document
DOI: 10.4230/OASIcs.ICCSW.2014.19
Identifying and inferring objects from textual descriptions of scenes from books

Authors: Andrew Cropper

Published in: OASIcs, Volume 43, 2014 Imperial College Computing Student Workshop

Abstract
Fiction authors rarely provide detailed descriptions of scenes, preferring the reader to fill in the details using their imagination. Therefore, to perform detailed text-to-scene conversion from books, we need to not only identify explicit objects but also infer implicit objects. In this paper, we describe an approach to inferring objects using Wikipedia and WordNet. In our experiments, we are able to infer implicit objects such as monitor and computer by identifying explicit objects such as keyboard.
Cite as

Andrew Cropper. Identifying and inferring objects from textual descriptions of scenes from books. In 2014 Imperial College Computing Student Workshop. Open Access Series in Informatics (OASIcs), Volume 43, pp. 19-26, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2014)

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@InProceedings{cropper:OASIcs.ICCSW.2014.19,
  author =	{Cropper, Andrew},
  title =	{{Identifying and inferring objects from textual descriptions of scenes from books}},
  booktitle =	{2014 Imperial College Computing Student Workshop},
  pages =	{19--26},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-76-7},
  ISSN =	{2190-6807},
  year =	{2014},
  volume =	{43},
  editor =	{Neykova, Rumyana and Ng, Nicholas},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ICCSW.2014.19},
  URN =		{urn:nbn:de:0030-drops-47690},
  doi =		{10.4230/OASIcs.ICCSW.2014.19},
  annote =	{Keywords: Text-to-Scene Conversion, Natural Language Processing, Artificial Intelligence}
}
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