Deceptive Autonomous Agents

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dc.contributor.authorSarkadi, Stefan
dc.date.accessioned2024-05-05T09:52:12Z
dc.date.available2024-05-05T09:52:12Z
dc.date.issued2020-01-09 10:31
dc.description.abstractRecent advances in Artificial Intelligence (AI) along with recent events revolving around the problem of fake news indicate new and critical potential threats to intelligence analysis, defence, security, and, by extension, to modern society in general. One such threat that we can derive from the development of AI is the emergence of malicious autonomous artificial agents that could develop their own reasons and strategies to act dishonestly. In order to be able to prevent or mitigate the malicious behaviour of deceptive artificial and autonomous agents, we must first understand how they might be designed, modelled, or engineered. In this work, we aim to model and study how artificial agents that deceive and detect deception can be engineered, as well as how such agents might impact the common good.
dc.description.sponsorshipKCL PhD Funding
dc.identifier.citationSarkadi, Stefan (2020). Deceptive Autonomous Agents. Cranfield Online Research Data (CORD). Presentation. https://doi.org/10.17862/cranfield.rd.11558397.v1
dc.identifier.doi10.17862/cranfield.rd.11558397.v1
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/21436
dc.publisherCranfield University
dc.rightsCC BY-NC 4.0
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0/
dc.subject'Deception'
dc.subject'Malicious AI'
dc.subject'Complex Reasoning'
dc.subject'DSDS19'
dc.subject'DSDS19 Technical Paper'
dc.subject'Artificial Intelligence and Image Processing not elsewhere classified'
dc.titleDeceptive Autonomous Agents
dc.typePresentation

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