How to (re)represent it?

Raggi, Daniel, Stapleton, Gem, Stockdill, Aaron, Jamnik, Mateja, Garcia, Grecia Garcia and Cheng, Peter C -H (2020) How to (re)represent it? International Conference on Tools for Artificial Intelligence (ICTAI), Virtual, 9-11 November 2020. Published in: Proceedings of the International Conference on Tools with Artificial Intelligence, ICTAI. 1224-1232. IEEE ISSN 1082-3409 ISBN 9781728192284

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Abstract

Choosing an effective representation is fundamental to the ability of the representation's user to exploit it for the intended purpose. The major contribution of this paper is to provide a novel, flexible framework, rep2rep, that can be used by AI systems to recommend effective representations. What makes an effective representation is determined by whether it expresses the necessary information, supports the execution of tasks, and reflects the user's cognitive abilities. In general, there is no single 'most effective' representation for every problem and every user, which makes it difficult to choose one from the plethora of possible representations. To address this, rep2rep includes: A domain-independent language for describing representations, algorithms that compute measures of informational suitability and overall cognitive cost, and uses these measures to recommend representations. We demonstrate the application of rep2rep in the probability domain. Importantly, our framework provides the foundations for personalised interaction with AI systems in the context of representation choice.

Item Type: Conference Proceedings
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
Schools and Departments: School of Engineering and Informatics > Informatics
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Date Deposited: 20 Sep 2021 09:20
Last Modified: 04 Mar 2022 16:45
URI: http://sro.sussex.ac.uk/id/eprint/101758

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