Domain Modelling in Computational Persuasion for Behaviour Change in Healthcare

February 27, 2018 Β· Declared Dead Β· πŸ› arXiv.org

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Authors Lisa Chalaguine, Emmanuel Hadoux, Fiona Hamilton, Andrew Hayward, Anthony Hunter, Sylwia Polberg, Henry W. W. Potts arXiv ID 1802.10054 Category cs.AI: Artificial Intelligence Citations 11 Venue arXiv.org Last Checked 4 months ago
Abstract
The aim of behaviour change is to help people to change aspects of their behaviour for the better (e.g., to decrease calorie intake, to drink in moderation, to take more exercise, to complete a course of antibiotics once started, etc.). In current persuasion technology for behaviour change, the emphasis is on helping people to explore their issues (e.g., through questionnaires or game playing) or to remember to follow a behaviour change plan (e.g., diaries and email reminders). However, recent developments in computational persuasion are leading to an argument-centric approach to persuasion that can potentially be harnessed in behaviour change applications. In this paper, we review developments in computational persuasion, and then focus on domain modelling as a key component. We present a multi-dimensional approach to domain modelling. At the core of this proposal is an ontology which provides a representation of key factors, in particular kinds of belief, which we have identified in the behaviour change literature as being important in diverse behaviour change initiatives. Our proposal for domain modelling is intended to facilitate the acquisition and representation of the arguments that can be used in persuasion dialogues, together with meta-level information about them which can be used by the persuader to make strategic choices of argument to present.
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