Automated Extension of Narrative Planning Domains with Antonymic Operators

Porteous, J, Lindsay, A, Read, J, Truran, M and Cavazza, M 2015, 'Automated Extension of Narrative Planning Domains with Antonymic Operators', in Bordini, Elkind, Weiss, Yolum (ed.) Proceedings of the 14th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2015), Istanbul, Turkey, 4-8 May 2015, pp. 1547-1555.


Document type: Conference Paper
Collection: Conference Papers

Title Automated Extension of Narrative Planning Domains with Antonymic Operators
Author(s) Porteous, J
Lindsay, A
Read, J
Truran, M
Cavazza, M
Year 2015
Conference name AAMAS 2015
Conference location Istanbul, Turkey
Conference dates 4-8 May 2015
Proceedings title Proceedings of the 14th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2015)
Editor(s) Bordini, Elkind, Weiss, Yolum
Publisher Association for Computing Machinery
Place of publication New York, United States
Start page 1547
End page 1555
Total pages 9
Abstract AI Planning has been widely used for narrative generation and the control of virtual actors in interactive storytelling. Planning models for such dynamic environments must include alternative actions which enable deviation away from a baseline storyline in order to generate multiple story variants and to be able to respond to changes that might be made to the story world. However, the actual creation of these domain models has been a largely empirical process with a lack of principled approaches to the definition of alternative actions. Our work has addressed this problem and in the paper we present a novel automated method for the generation of interactive narrative domain models from existing non-interactive versions. Central to this is the use of actions that are contrary to those forming the baseline plot within a principled mechanism for their semi-automatic production. It is important that such newly created domain content should still be human-readable and to this end labels for new actions and predicates are generated automatically using antonyms selected from a range of on-line lexical resources. Our approach is fully implemented in a prototype system and its potential demonstrated via both formal experimental evaluation and user evaluation of the generated action labels.
Subjects Artificial Intelligence and Image Processing not elsewhere classified
Keyword(s) Virtual Agents
Interactive Storytelling
Narrative Modelling
Planning
Copyright notice Copyright © 2015 by the International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved.
ISBN 9781450334136
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