Automated narrative planning model extension

Julie Porteous, João F. Ferreira, Alan Lindsay, Marc Cavazza

Research output: Contribution to journalArticlepeer-review

Abstract

Interactive Narrative is an emerging application of automated planning, in which a planning domain is used to generate a consistent chain of narrative actions that constitute a plot structure. The task of creating narrative planning domains has been identified as a bottleneck which is hampering further development of the field. This stems from the difficulties faced by humans authoring such planning domains due to the need to provide the range of alternative content, such as actions, which are required to support the important properties of diversity and robustness. Narrative planning domains must be capable of generating diverse sets of narratives to ensure system replayability, and they must also be able to respond robustly in the face of narrative execution failure due to user interaction. In this paper, we introduce a novel approach to the development of narrative planning domains based on the automatic expansion of a baseline planning domain through application of principled operations applied to both operators and predicates. We overview two such operations in this paper. The first of these, anton for antonymic operators, is based on the generation of contrary operators that can be invoked in the face of action failure, and whose structure is derived from a model of state transitions triggered by the original operator. Since the intention is for additional operators to be incorporated to the baseline, human-authored, domain model, the generated contents should be human-readable. This is achieved by using combined linguistic resources to access antonyms of predicates occurring inside operators, and parsing them from and into hyphenated units. The second operation, part of the same approach, referred to as thype, generates variants of operators by exploring type hierarchies for the main concepts associated with individual operators; the resulting concepts being fully integrated into a new operator’s structure. Our evaluation procedures are directly derived from the target properties of narrative planning domains, which are diversity and robustness, the former being measured through plot diversity and the latter, plot continuation following planned action execution failure. We used published narrative domains as datasets for these evaluations. Results demonstrated strong generative ability, and even more significant plan completion following action failure. Moreover, our evaluation demonstrates the synergic nature of anton and thype when applied simultaneously. Future work will focus on improving the integration of anton and thype operations through better balance between linguistic and conceptual hierarchies.

Original languageEnglish
Article number19
JournalAutonomous Agents and Multi-Agent Systems
Volume35
Issue number2
Early online date7 May 2021
DOIs
Publication statusPublished - Oct 2021

Keywords

  • Domain modeling
  • Narrative planning
  • Virtual agents

ASJC Scopus subject areas

  • Artificial Intelligence

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