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Extending narrative planning domains with linguistic resources

Extending narrative planning domains with linguistic resources

Porteous, Julie, Ferreira, Joao F., Lindsay, Alan and Cavazza, Marc ORCID: 0000-0001-6113-9696 (2020) Extending narrative planning domains with linguistic resources. In: AAMAS '20: Proceedings of the 19th International Conference on Autonomous Agents and MultiAgent Systems. International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS), pp. 1081-1089. ISBN 978-1450375184

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Abstract

Interactive Narrative (IN) is an emerging application of planning for control of virtual character behaviours. Despite popularity in research, more widespread adoption of planning has been hindered by the difficulty of authoring planning domain models as INs require models which are robust to dynamic environments and capable of generating a diversity of solutions. To reduce this authoring burden we explored automated extension of partially developed planning domains to address robustness and diversity. We introduce a novel algorithm, thype, which proposes additional types of characters and objects to extend a domain model. The extensions increase robustness by enlarging the range of ways to enact planned behaviours. In the paper we embed thype within a modular and extensible framework that allows multiple off-line generated extensions to be combined. We present results of a user study that show thype suggestions are plausible. We also empirically demonstrate the ability of thype extensions to increase the robustness of the models, demonstrate the modular nature of our extension framework by combining thype with another extension approach dedicated to recovery from plan failure and present results which show that enhanced performance results from combining multiple extensions.

Item Type: Conference Proceedings
Title of Proceedings: AAMAS '20: Proceedings of the 19th International Conference on Autonomous Agents and MultiAgent Systems
Additional Information: Conference held at Auckland, New Zealand, May 9–13, 2020, IFAAMAS.
Uncontrolled Keywords: socially interactive agents, virtual humans, interactive narrative
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty / Department / Research Group: Faculty of Liberal Arts & Sciences
Faculty of Liberal Arts & Sciences > School of Computing & Mathematical Sciences (CAM)
Last Modified: 26 Nov 2020 22:34
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
Selected for REF2021: None
URI: http://gala.gre.ac.uk/id/eprint/27127

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