SAsSy - Making Decisions Transparent with Argumentation and Natural Language Generation

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Demo: Making Plans Scrutable with Argumentation and Natural Language Generation.

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Production of Referring Expressions for an Unknown Audience : a Computational Model of Communal Common Ground

The research reported in this article is based on the Ph.D. project of Dr. RK, which was funded by the Scottish Informatics and Computer Science Alliance (SICSA). KvD acknowledges support from the EPSRC under the RefNet grant (EP/J019615/1).Peer reviewedPublisher PD

SAsSy – Scrutable Autonomous Systems

Abstract. An autonomous system consists of physical or virtual systems that can perform tasks without continuous human guidance. Autonomous systems are becoming increasingly ubiquitous, ranging from unmanned vehicles, to robotic surgery devices, to virtual agents which collate and process information on the internet. Existing autonomous systems are opaque, limiting their usefulness in many situations. In order to realise their promise, techniques for making such autonomous systems scrutable are therefore required. We believe that the creation of such scrutable autonomous systems rests on four foundations, namely an appropriate planning representation; the use of a human understandable reasoning mechanism, such as argumentation theory; appropriate natural language generation tools to translate logical statements into natural ones; and information presentation techniques to enable the user to cope with the deluge of information that autonomous systems can provide. Each of these foundations has its own unique challenges, as does the integration of all of these into a single system.

Audience Design in the Generation of References to Famous People

This paper seeks to fill a gap in existing computational models of the production of referring expressions, by addressing situations in which speakers have difficulty assessing what information is available to their audience. The paper describes a two-part experiment where speakers were given the name of a famous person and had to create a description that would enable a hearer to identify the person, and hearers used the created descriptions to guess the name of the described person. The experiment compares how confident hearers are that they have identified the referent and how well speakers can estimate this confidence. The results of the experiment suggest that speakers do not overestimate hearers ’ confidence as the psycholinguistic literature had led us to expect

Scrutable Plan Enactment via Argumentation and Natural Language Generation (Demonstration)

ABSTRACT Autonomous systems suffer from opacity due to the potentially large number of sophisticated interactions among many parties and how these influence the outcomes of the systems. It is very difficult for humans to scrutinise, understand and, ultimately, work with such systems. To address this shortcoming, we developed a demonstrator which uses formal argumentation techniques, coupled with natural language generation, to explain the rationale of a hybrid software-human many-party joint plan during its enactment