KMi Seminars
Arguing for Intelligence: The Roles of Argumentation in AI
This event took place on Thursday 09 December 2004 at 14:15

Dr Chris Reed Department of Applied Computing, University of Dundee, Scotland

In contrast to the formal analysis of reasoned argument, pursued by mathematicians since the turn of the century, a small band of philosophers and linguists have been attempting to reconcile a formal, powerful analysis with the demands of real world, natural argumentation. The endeavour is termed 'argumentation theory', under which head are collected fallacy theory, enthymeme reconstruction, subjective plausibility, dialectics and rhetoric, amongst others. These various techniques and subfields have turned out to have a wide range of applications in artificial intelligence. Coordination in multi-agent systems, persuasive text generation in computational linguistics, e-democracy and computer-supported collaborative work, defeasible and other nonclassical logics, legal support systems and other areas have all made use of various aspects of argumentation theory. In this talk, I shall focus upon projects under way at Dundee, not only to show a variety of applications of argumentation theory in many of these domains, but also to demonstrate the potential for coherence and reuse between them.

Replay should be available within one week of the event.

 
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Multimedia and Information Systems is...


Multimedia and Information Systems
Our research is centred around the theme of Multimedia Information Retrieval, ie, Video Search Engines, Image Databases, Spoken Document Retrieval, Music Retrieval, Query Languages and Query Mediation.

We focus on content-based information retrieval over a wide range of data spanning form unstructured text and unlabelled images over spoken documents and music to videos. This encompasses the modelling of human perception of relevance and similarity, the learning from user actions and the up-to-date presentation of information. Currently we are building a research version of an integrated multimedia information retrieval system MIR to be used as a research prototype. We aim for a system that understands the user's information need and successfully links it to the appropriate information sources, be it a report or a TV news clip. This work is guided by the vision that an automated knowledge extraction system ultimately empowers people making efficient use of information sources without the burden of filing data into specialised databases.

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