Learning to Learn in Collective Adaptive Systems: Mining Design Patterns for Data-driven Reasoning

D'Angelo, M, Ghahremani, S, Gerasimou, S et al. (4 more authors) (2020) Learning to Learn in Collective Adaptive Systems: Mining Design Patterns for Data-driven Reasoning. In: 2020 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C). 2020 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C), 17-21 Aug 2020, Washington, DC, USA. IEEE , pp. 121-126. ISBN 9781728184142

Abstract

Metadata

Item Type: Proceedings Paper
Authors/Creators:
  • D'Angelo, M
  • Ghahremani, S
  • Gerasimou, S
  • Grohmann, J
  • Nunes, I
  • Tomforde, S
  • Pournaras, E
Copyright, Publisher and Additional Information:

© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Keywords: Electronic mail, Cognition, Adaptive systems, Systematics, Decision trees, Bibliographies, Complexity theory
Dates:
  • Published: 15 September 2020
  • Published (online): 15 September 2020
  • Accepted: 12 July 2020
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 22 Apr 2021 09:14
Last Modified: 22 Apr 2021 09:14
Status: Published
Publisher: IEEE
Identification Number: 10.1109/acsos-c51401.2020.00042
Open Archives Initiative ID (OAI ID):

Export

Statistics