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«UNIVERSITY OF CALIFORNIA, SAN DIEGO Theory and Technology for Computational Narrative: An Approach to Generative and Interactive Narrative with Bases ...»

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“Computational narratology,” in the sense employed occasionally by the author and Joseph Goguen, is deeply influenced by the cognitive linguistics approach to narrative, and provides techniques from computer science to provide a language to describe cognitive insights and to implement narrative effects of the type analyzed in discourse narratology.

This approach reflects a paradigm shift in cognitive science away from elegant formal views of language that are not necessarily cognitively grounded (or even plausible), toward grounding in empirical results regarding cognitive phenomena underlying language. This computational approach to narrative also represents a paradigm shift in computer science. The computational narrative system presented in this dissertation does not attempt to implement a model of creativity (human or computer). Instead, it aims to provide a language for representing the human author’s expressive intentions along with subjective and constructive possibilities for user interaction and content generation. That is, the goal is to enable a human author to construct computational narratives featuring semantic underpinnings informed by cognitive science, and all of the potential for interpretively meaningful interaction and generation that such an underpinning provides. Human narrative imagining, conceptual blending, and related processes allow for user and author to negotiate meanings. The underlying computational structures an algorithms merely exploit regularities of such human cognitive processes, but do not simulate them.

1.2 Contributions The research described here consists of theoretical and technical support for, and implementations of, narrative computational media works with the following characteristics: generative content, semantics based interaction, reconfigurable narrative structure, and strong cognitive and socio-cultural grounding.

Generative content means that the system should be able to compose new content from media elements (in the forms of text, computer graphics, audio, or other media) on the fly. The GRIOT system, one of the results of this effort, provides an example of such generation. (Harrell, 2005a, 2005b, 2007) It has been used to implement computational poetry that generates a new narrative poem with fixed themes but varying metaphors upon each execution. This computational poetry is implemented on the basis of several knowledge bases entered by the author of a computational poem. The author constructs a knowledge base of domains (sets of typed binary relations), a narrative structure implemented as a new type of automaton called a “probabilistic bounded transition stack machine” or “Event Structure Machine,” a knowledge base of textual templates organized according to narrative type and featuring variables that can be replaced with generated content. (Goguen & Harrell, 2007b; Harrell, 2006) A key aspect is that the author defines the semantic rules that determine how content is generated.

Generativity is enabled by the Alloy system. Central to Alloy is an algorithm that implements key aspects of Gilles Fauconnier and Mark Turner’s theory of conceptual blending; it is also the first implementation of Joseph Goguen’s algebraic semiotics approach to blending (in turn, the first formal mathematical approach to blending). (Fauconnier & Turner, 2002; Goguen, 1998) Alloy takes in a data structure called an “input diagram” consisting of data structures representing Fauconnier and Turner’s conceptual spaces and mappings between them. Alloy returns an output diagram consisting of a “blended” conceptual space that integrates elements from conceptual spaces in the input diagram, and mappings to the blended conceptual space. Alloy, however, is not considered to model human cognitive processing. It is seen as a system to allow a researcher to formally describe conceptual spaces empirically determined or hypothesized by cognitive science researchers and to explore structural combinations of the conceptual spaces. As such, it is not intended as an “artificial intelligence” project, but rather as a system that allows researchers to invoke the utility of computational experimentation when appropriate, while respecting the limitations of computational models for describing human conceptual processes. The formalization used in Alloy and GRIOT is based in Joseph Goguen’s algebraic semiotics, which uses algebraic semantics and specification to describe sign systems.

Semantics-based interaction means that (1) media elements are structured according to the meaning of its content, and (2) user interaction can affect content of a computational narrative in a way that produces new meanings that are constrained by the system's author. “Meaning” in this case means that the author has provided formal descriptions of domains and concepts (as described above) pertinent to the media elements and authorial intent.

Reconfigurable narrative structure means that the formal structure of a computational narrative can be dynamically restructured, either according to user interaction, or upon execution of the system as in the case of narrative generation. The “Event Structure Machine” is the component that affords reconfigurable narrative structure. (Goguen & Harrell, 2007b; Harrell, 2006) Strong cognitive and socio-cultural grounding here implies that despite the use of formal descriptions of semantic concepts, meaning is considered to be dynamically constructed, distributed among our selves and our artifacts, situated in social contexts, and embodied in our physical experiences. (Fauconnier & Turner, 2002; Hutchins, 2000; Lave & Wenger, 1991; Varela, Thomson, & Rosch, 1991). The formalizations used also are inspired by, and respect, cognitive linguistics theories with such notions of meaning, and in practice a system author must be sensitive to these issues to effectively utilize the technical framework provided. Furthermore, the notion of narrative here is emphatically not biased toward one particular cultural model. The architecture is layered so that, atop a technical layer that provides an authoring platform, a cultural producer can implement her or his desired model of narrative (whether Labov’s empirically based narrative structure of personal experience from sociolinguistics, or Gerald Vizenor’s narrative theory of Native American trickster tales). (Harrell, 2005a; Labov, 1972; Vizenor, 1989) Toward all of these ends, the work here also contributes to the theories of algebraic semiotics and cognitive semantics by developing a blending-based notion of style and some mathematics in order to extend the algebraic semiotics model to allow for generativity and the specific applications described above.

1.3 Dissertation Outline A challenge, and boon, of an interdisciplinary dissertation is the fact that such work invites readers from differing disciplinary backgrounds to consider it. While a boon, of course, is that the work may be influential and interesting to people of varying intellectual traditions, one challenge is that necessary background for one audience may prove to be either rudimentary, advanced, or auxiliary for another.

Worse, each tradition carries with it a set of values, methods, and goals which may be challenging to integrate, and at worst may be incommensurable.

The challenge is handled in this dissertation by defining an overarching set of goals and presenting individual results on the path toward those goals in the language of the discipline to which the results are most relevant (e.g., the description of the Alloy algorithm is presented within the tradition of computer science and engineering). At times, a hybrid discourse is constructed because a natural alignment between the goals of multiple disciplines is formed (e.g., the work in computational poetry speaks to an integrated framework of creative writing, literary theory, cognitive science, and computer science). At other times, it is necessary to clearly articulate the relationship between disciplines and that clear articulation becomes a new theoretical result (e.g., clearly describing the role of computational modeling for scientific experimentation with conceptual blending theory). At other times again, it is important to offer an introductory account of an entire field of study because practitioners from one field may have had no previous exposure to the field (e.g., some practitioners from engineering may have had little exposure to semiotics theories).

This dissertation attempts to balance all of these concerns into a coherent and compelling text. A gentle request is made to the reader to put aside disciplinary biases and submit to the possibility of integrated interdisciplinary goals. The read will be more pleasurable, and in that light I believe the contributions here can be most sensitively received and evaluated.

Bearing in mind the interdisciplinary relationships described above, Chapter 2 of this dissertation describes the theoretical foundations of the dissertation’s contributions. Section 2.1 and its subsections describe various approaches to narrative ranging from sociolinguistics to experimental literature, and including various forms of narrative in computational media. By presenting this overview of approaches and antecedent computational narrative forms, Section 2.1 comprises a review of literature that influences the approach here and a vision of how they are integrated into a coherent research project.

Section 2.2 presents ideas from the enterprise of cognitive linguistics within the field of cognitive science that are central to the research problem here.

This account is aimed primarily at readers outside of the field of cognitive linguistics and helps to situate the theories developed within that enterprise in relation to earlier theories. The account of cognitive linguistics is also aimed at relating the aims of the enterprise to issues in linguistics that have proven influential in computer science and artificial intelligence. To better situate the empirical foundations and theoretical import of the specific cognitive linguistics theories, Subsection 2.2.1 describes a high level view of the philosophical commitments and historical context of the cognitive linguistics enterprise. Subsection 2.2.2 describes methods used in cognitive linguistics. Subsection 2.2.3 presents an overview of the influential theory of metaphor. Subsection 2.2.4 presents an overview of conceptual blending theory, one of the central theoretical influences on the research here. Conceptual blending theory is a young and developing theory and, as such, is not without its controversies.

Subsection 2.2.5 presents some of the central controversies and criticisms of the theory and offers some remarks on them. Since one of the results of this dissertation is an algorithm that implements aspects of conceptual blending, Subsection 2.2.6 presents a review of other work that applies computational techniques to conceptual blending and related areas in cognitive science.

Section 2.3 presents Joseph Goguen’s theory of algebraic semiotics.


1998) Together we pioneered the use of his theory toward the purpose of computational narrative. Indeed this theory forms the bridge between cognitive science and computer science used here. It also forms the bridge between computer science and socio-cultural and artistic meaning, so it is one of the most crucial aspects of the theory and technology underlying all of the results of this dissertation.

Algebraic semiotics is used to formalize conceptual blending theory, but just as important is the philosophy underlying algebraic semiotics, i.e., formalization is used only as a descriptive (and implementable) tool. Language and meaning themselves are not viewed as formal by nature, and this work respects the insights of the cognitive linguistics enterprise in which human meaning is considered to be embodied, distributed, and situated. Formalization alone does not offer any greater cognitive plausibility to research results. This balance between formal methods that are necessary in computer science and deep understanding of the socially, culturally, bodily, and cognitively constructed nature of meaning is a reason why the algebraic semiotics approach is desirable for computational narrative applications. This section is not merely a literature review, but includes new results by Joseph Goguen and the author.

Chapter 3 presents the Alloy system, including its knowledge (data) representation structures in Section 3.1, and its algorithm for conceptual blending in Section 3.2. Section 3.3 presents an account of the limitations of the system and how, in part, these limitations reflect the natural limitations of computational methods as tools for cognitive linguistics research. In this regard, the algorithm itself, and the theoretical discussion of its relationship to human meaning construction, are both presented as important results.

Chapter 4 presents the GRIOT system for implementing computational narratives. Section 4.1 formally describes the problem of narrative construction within the framework of algebraic semiotics as the blending of structures. Section 4.2 presents a detailed view of the GRIOT architecture. Section 4.3 describes various levels of use including multiple levels authorship, readership, performance (and uses that exist in-between all three) enabled by GRIOT. Section 4.4 presents several examples of computational poetry as case studies implemented with GRIOT. Each of these case studies raises unique theoretical issues and introduces particular implementation advances. Section 4.4 concludes with remarks toward evaluating the “success” of the case studies, understanding that engineering and scientific models of success may not apply to aesthetic works.

Chapter 5 concludes the dissertation with a recapitulation of the results and contributions, remarks on how the approach here broadly can lead to new accounts of “style” in aesthetic and cultural expression, and reflection on the possibilities and

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