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dc.contributor.authorDe Silva, Lavindra
dc.contributor.authorMycroft, A
dc.date.accessioned2022-05-25T23:30:11Z
dc.date.available2022-05-25T23:30:11Z
dc.date.issued2022-06-08
dc.identifier.issn0951-5666
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/337476
dc.description.abstractA key focus in AI is building machines and software capable of being autonomous, especially in complex and dynamic environments where, e.g., self driving cars, trading systems, and social care robots operate. Such autonomous systems are able to independently make decisions and act on them with limited human intervention, balancing the pursuit of long-term goals (proactiveness) with rapid response to environmental changes (reactiveness) (Fisher et al. 2021). The notion of an autonomous system is synonymous with the notion of an ‘autonomous software agent’ (Fisher et al. 2021), and a class of domain-specific language called an Agent-Oriented Programming Language (AOPL) has proved to be one of the most successful approaches to building such systems. AOPLs provide abstractions over Object-Oriented Programming, by modelling complex systems through the ‘intentional stance’ – human-like mental attitudes such as beliefs, goals, and intentions, enabling users understand, explain, predict, and program behaviour by abstracting from the detail (objects, attributes, etc.). Indeed, giving people this ability helps build trustworthy AI systems, particularly those that people can trust to have been designed and programmed to be lawful, ethical, and robust, ensuring adherence to applicable laws, regulations, and ethical principles, and operating in a safe, secure and reliable manner.
dc.publisherSpringer Science and Business Media LLC
dc.rightsAll Rights Reserved
dc.rights.urihttp://www.rioxx.net/licenses/all-rights-reserved
dc.titleToward trustworthy programming for autonomous concurrent systems
dc.typeArticle
dc.publisher.departmentDepartment of Engineering
dc.date.updated2022-05-17T10:46:46Z
prism.publicationNameAI and Society
dc.identifier.doi10.17863/CAM.84890
dcterms.dateAccepted2022-04-13
rioxxterms.versionofrecord10.1007/s00146-022-01463-6
rioxxterms.versionAM
dc.identifier.eissn1435-5655
rioxxterms.typeJournal Article/Review
cam.issuedOnline2022-06-08
cam.orpheus.successMon Jul 11 08:50:17 BST 2022 - Embargo updated*
cam.orpheus.success2022/07/29
cam.orpheus.counter5
cam.depositDate2022-05-17
pubs.licence-identifierapollo-deposit-licence-2-1
pubs.licence-display-nameApollo Repository Deposit Licence Agreement
rioxxterms.freetoread.startdate2023-06-08


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