Linear Logic Programming for Narrative Generation

Chris Martens, Anne-Gwenn Bosser, João F. Ferreira, Marc Cavazza

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Abstract

In this paper, we explore the use of Linear Logic programming for story generation. We use the language Celf to represent narrative knowledge, and its own querying mechanism to generate story instances, through a number of proof terms. Each proof term obtained is used, through a resource-flow analysis, to build a directed graph where nodes are narrative actions and edges represent inferred causality relationships. Such graphs represent narrative plots structured by narrative causality. This approach is a candidate technique for narrative generation which unifies declarative representations and generation via query and deduction mechanisms.
Original languageEnglish
Pages (from-to)427-432
JournalLecture Notes in Artificial Intelligence
Volume8148
DOIs
Publication statusPublished - 2013
Event12th International Conference - Logic Programming and Nonmonotonic Reasoning - Corunna, Spain
Duration: 15 Sep 201319 Sep 2013
Conference number: 12

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Logic programming
Directed graphs

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Martens, Chris ; Bosser, Anne-Gwenn ; Ferreira, João F. ; Cavazza, Marc. / Linear Logic Programming for Narrative Generation. In: Lecture Notes in Artificial Intelligence. 2013 ; Vol. 8148. pp. 427-432.
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Linear Logic Programming for Narrative Generation. / Martens, Chris; Bosser, Anne-Gwenn; Ferreira, João F.; Cavazza, Marc.

In: Lecture Notes in Artificial Intelligence, Vol. 8148, 2013, p. 427-432.

Research output: Contribution to journalConference articleResearchpeer-review

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