Types of computational self-awareness and how we might implement them

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Computing systems increasingly comprise large numbers of heterogeneous subsystems, each with their own local perspective and goals, connected in dynamic networks, and interacting with each other and humans in ways which are difficult to predict. Nevertheless, users engaging with different parts of the system still expect high performance, reliability, security and other qualities, provided in a way that is robust or adaptive in the presence of unforeseen changes (including to users, the network, physical environment or the system itself). Examples of systems which are facing this challenge are wide-ranging and include robot swarms, personal devices, web services and sensor networks. In all these cases, advanced levels of autonomous behaviour can enable the system to adapt itself at run time, by learning behaviours in real time, appropriate to changing conditions.

LanguageEnglish
Title of host publicationCODES '16: Proceedings of the eleventh IEEE/ACM/IFIP International Conference on Hardware/Software Codesign and System Synthesis
PublisherACM
Number of pages2
ISBN (Electronic)978-1-4503-4483-8
DOIs
Publication statusPublished - 1 Oct 2016
Event11th IEEE/ACM/IFIP International Conference on Hardware/Software Codesign and System Synthesis - Pittsburgh, United States
Duration: 1 Oct 20167 Oct 2016

Conference

Conference11th IEEE/ACM/IFIP International Conference on Hardware/Software Codesign and System Synthesis
Abbreviated titleCODES/ISSS ’16
CountryUnited States
CityPittsburgh
Period1/10/167/10/16

Fingerprint

Web services
Sensor networks
Robots

Bibliographical note

-

Cite this

Lewis, P. R. (2016). Types of computational self-awareness and how we might implement them. In CODES '16: Proceedings of the eleventh IEEE/ACM/IFIP International Conference on Hardware/Software Codesign and System Synthesis [a35] ACM. https://doi.org/10.1145/2968456.2973273
Lewis, Peter R. / Types of computational self-awareness and how we might implement them. CODES '16: Proceedings of the eleventh IEEE/ACM/IFIP International Conference on Hardware/Software Codesign and System Synthesis. ACM, 2016.
@inproceedings{6da8a909b7524693b3e44d1d4ab4c4bd,
title = "Types of computational self-awareness and how we might implement them",
abstract = "Computing systems increasingly comprise large numbers of heterogeneous subsystems, each with their own local perspective and goals, connected in dynamic networks, and interacting with each other and humans in ways which are difficult to predict. Nevertheless, users engaging with different parts of the system still expect high performance, reliability, security and other qualities, provided in a way that is robust or adaptive in the presence of unforeseen changes (including to users, the network, physical environment or the system itself). Examples of systems which are facing this challenge are wide-ranging and include robot swarms, personal devices, web services and sensor networks. In all these cases, advanced levels of autonomous behaviour can enable the system to adapt itself at run time, by learning behaviours in real time, appropriate to changing conditions.",
author = "Lewis, {Peter R.}",
note = "-",
year = "2016",
month = "10",
day = "1",
doi = "10.1145/2968456.2973273",
language = "English",
booktitle = "CODES '16: Proceedings of the eleventh IEEE/ACM/IFIP International Conference on Hardware/Software Codesign and System Synthesis",
publisher = "ACM",
address = "United States",

}

Lewis, PR 2016, Types of computational self-awareness and how we might implement them. in CODES '16: Proceedings of the eleventh IEEE/ACM/IFIP International Conference on Hardware/Software Codesign and System Synthesis., a35, ACM, 11th IEEE/ACM/IFIP International Conference on Hardware/Software Codesign and System Synthesis, Pittsburgh, United States, 1/10/16. https://doi.org/10.1145/2968456.2973273

Types of computational self-awareness and how we might implement them. / Lewis, Peter R.

CODES '16: Proceedings of the eleventh IEEE/ACM/IFIP International Conference on Hardware/Software Codesign and System Synthesis. ACM, 2016. a35.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - Types of computational self-awareness and how we might implement them

AU - Lewis, Peter R.

N1 - -

PY - 2016/10/1

Y1 - 2016/10/1

N2 - Computing systems increasingly comprise large numbers of heterogeneous subsystems, each with their own local perspective and goals, connected in dynamic networks, and interacting with each other and humans in ways which are difficult to predict. Nevertheless, users engaging with different parts of the system still expect high performance, reliability, security and other qualities, provided in a way that is robust or adaptive in the presence of unforeseen changes (including to users, the network, physical environment or the system itself). Examples of systems which are facing this challenge are wide-ranging and include robot swarms, personal devices, web services and sensor networks. In all these cases, advanced levels of autonomous behaviour can enable the system to adapt itself at run time, by learning behaviours in real time, appropriate to changing conditions.

AB - Computing systems increasingly comprise large numbers of heterogeneous subsystems, each with their own local perspective and goals, connected in dynamic networks, and interacting with each other and humans in ways which are difficult to predict. Nevertheless, users engaging with different parts of the system still expect high performance, reliability, security and other qualities, provided in a way that is robust or adaptive in the presence of unforeseen changes (including to users, the network, physical environment or the system itself). Examples of systems which are facing this challenge are wide-ranging and include robot swarms, personal devices, web services and sensor networks. In all these cases, advanced levels of autonomous behaviour can enable the system to adapt itself at run time, by learning behaviours in real time, appropriate to changing conditions.

UR - http://www.scopus.com/inward/record.url?scp=85006868257&partnerID=8YFLogxK

UR - https://dl.acm.org/citation.cfm?doid=2968456.2973273

U2 - 10.1145/2968456.2973273

DO - 10.1145/2968456.2973273

M3 - Conference contribution

BT - CODES '16: Proceedings of the eleventh IEEE/ACM/IFIP International Conference on Hardware/Software Codesign and System Synthesis

PB - ACM

ER -

Lewis PR. Types of computational self-awareness and how we might implement them. In CODES '16: Proceedings of the eleventh IEEE/ACM/IFIP International Conference on Hardware/Software Codesign and System Synthesis. ACM. 2016. a35 https://doi.org/10.1145/2968456.2973273