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Output details

11 - Computer Science and Informatics

Imperial College London

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Output 111 of 201 in the submission

Output title

Learning Revised Models For Planning In Adaptive Systems

Type

E - Conference contribution

DOI

10.1109/ICSE.2013.6606552

Name of conference/published proceedings

35th IEEE/ACM International Conference on Software Engineering

Volume number

Issue number

First page of article

ISSN of proceedings

Year of publication

2013

URL

Number of additional authors

Additional information

<09> Model revision is extremely challenging. This paper demonstrates the benefits of integrating ILP, model checking and plan synthesis in adaptive systems for revising models which can be incomplete, inaccurate and/or out of date. The approach uses non-monotonic probabilistic rule learning (NoMPRoL) to find hypotheses that explain the observations and conditions under which they occur. Updated models are used to generate new plans. Research has led to continuing collaboration with the NII Japan (Prof. Honiden http://research.nii.ac.jp/~honiden/) and was presented at the flagship software engineering conference, ICSE: Acceptance 18.5%/461. Preliminary work was part of the keynote talk, ICSE 2012.

Interdisciplinary

Cross-referral requested

Research group

B - Distributed Software Engineering

Citation count

Proposed double-weighted

Double-weighted statement

Reserve for a double-weighted output

Non-English

English abstract