Linear Logic Programming for Narrative Generation
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. Building on previous work evidencing the suitability of Linear Logic as a conceptual model of action and change for narratives, we explore the conditions under which these representations can be operationalized through Linear Logic Programming techniques. This approach is a candidate technique for narrative generation which uniﬁes declarative representations and generation via query and deduction mechanisms.