Logic-Based Inductive Synthesis of Efficient Programs

Cropper, Andrew

Logic-Based Inductive Synthesis of Efficient Programs

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Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence. Pages 3980-3980.

Abstract

Inductive programming approaches typically rely on an Occamist bias to select hypotheses with minimal textual complexity. This approach, however, fails to distinguish between the efficiencies of hypothesised programs, such as merge sort (O(n log n)) and bubble sort (O(n2)). We address this issue by introducing techniques to learn logic programs with minimal resource complexity. We describe an algorithm proven to learn minimal resource complexity robot strategies, and we propose future work to generalise the approach to a broader class of programs.

Andrew Cropper. 2016. Logic-Based Inductive Synthesis of Efficient Programs. In Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, IJCAI-16. IJCAI, 3980–3980. https://ijcai.org/proceedings/2016/564

@inproceedings{ijcai2016p564,
  title     = {Logic-Based Inductive Synthesis of Efficient Programs},
  author    = {Cropper, Andrew},
  booktitle = {Proceedings of the Twenty-Fifth International Joint Conference on
               Artificial Intelligence, {IJCAI-16}},
  publisher = {AAAI Press / International Joint Conferences on Artificial Intelligence},
  editor    = {Subbarao Kambhampati},
  pages     = {3980--3980},
  year      = {2016},
  month     = {7},
  url       = {https://ijcai.org/proceedings/2016/564},
}

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TI  - Logic-Based Inductive Synthesis of Efficient Programs
AU  - Cropper, Andrew
T2  - Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, IJCAI-16
PB  - AAAI Press / International Joint Conferences on Artificial Intelligence
PY  - 2016
SP  - 3980
EP  - 3980
UR  - https://ijcai.org/proceedings/2016/564
ER  -