Some Empirical Criteria for Attributing Creativity to a Computer Program

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Towards Generating Stylistic Dialogues for Narratives using Data-Driven Approaches

Recently, there has been a renewed interest in generating dialogues for narratives. Within narrative dialogues, their structure and content are essential, though style holds an important role as a mean to express narrative dialogue through telling stories. Most existing approaches of narrative dialogue generation tend to leverage hand-crafted rules and linguistic-level styles, which lead to limitations in their expressivity and issues with scalability. We aim to investigate the potential of generating more stylistic dialogues within the context of narratives. To reach this, we propose a new approach and demonstrate its feasibility through the support of deep learning. We also describe this approach using examples, where story-level features are analysed and modelled based on a classification of characters and genres

Planning Technologies for Interactive Storytelling

Since AI planning was first proposed for the task of narrative generation in interactive storytelling (IS), it has emerged as the dominant approach in this field. This chapter traces the use of planning technologies in this area, considers the core issues involved in the application of planning technologies in IS, and identifies some of the remaining challenges

Four PPPPerspectives on Computational Creativity in theory and in practice

Computational creativity is the modelling, simulating or replicating of creativity computationally. In examining and learning from these `creative systems', from what perspective should the creativity of a system be considered? Are we interested in the creativity of the system's output? Or of its creative processes? Features of the system? Or how it operates within its environment? Traditionally computational creativity has focused more on creative systems' products or processes, though this focus has widened recently. Creativity research offers the Four Ps of creativity: Person/Producer, Product, Process and Press/Environment. This paper presents the Four Ps, explaining each in the context of creativity research and how it relates to computational creativity. To illustrate the usefulness of the Four Ps in taking broader perspectives on creativity in its computational treatment, the concepts of novelty and value are explored using the Four Ps, highlighting aspects of novelty and value that may otherwise be overlooked. Analysis of recent research in computational creativity finds that although each of the Four Ps appears in the body of computational creativity work, individual pieces of work often do not acknowledge all Four Ps, missing opportunities to widen their work's relevance. We can see, though, that high-status computational creativity papers do typically address all Four Ps. This paper argues that the broader views of creativity afforded by the Four Ps is vital in guiding us towards more comprehensively useful computational investigations of creativity. This paper is available for free download during September 2016 at http://tandfonline.com/doi/full/10.1080/09540091.2016.115186

Argument-Based Case Revision in CBR for Story Generation

This paper presents a new approach to case revision in casebased reasoning based on the idea of argumentation. Previous work on case reuse has proposed the use of operations such as case amalgamation (or merging), which generate solutions by combining information coming from different cases. Such approaches are often based on exploring the search space of possible combinations looking for a solution that maximizes a certain criteria. We show how Revise can be performed by arguments attacking specific parts of a case produced by Reuse, and how they can guide and prevent repeating pitfalls in future cases. The proposed approach is evaluated in the task of automatic story generation. © Springer International Publishing Switzerland 2015.This research was partially supported by projects CoInvent (FET-Open grant 611553) and NASAID (CSIC Intramural 201550E02Peer Reviewe

Modeling Literary Style for Semi-Automatic Generation of Poetry

The generation of formal poetry involves both complex creativity - usually exercised by a human poet - and strict algorithmic restrictions regarding the metrical structure of the poem - determined by literary tradition. Starting from a generating system that enforces automatically the metrical restrictions, this paper presents a model for the literary style of a user based on four key features for user preferences - word selection, language structures, poem planning, and restrictions on realisation - governing the generation of poetry from input data provided by the user - a prose paraphrase of the intended message, a task specific vocabulary, and a corpus of construction patterns. The system exploits the CBR paradigm as a means to evolve a case base (a vocabulary / construction pattern grouping) that effectively models the style of a specific user as a result of multiple iterations through the CBR cycle

Poetry generation in COLIBRI

Abstract. CBROnto is an ontology that incorporates common Case-Based Reasoning (CBR) terminology and serves as a domain-independent framework to design CBR applications. It is the core of COLIBRI, an environment to assist during the design of knowledge intensive CBR systems that combine cases with various knowledge types and reasoning methods. CBROnto captures knowledge about CBR tasks and methods, and aims to unify case specific and general domain knowledge representational needs. CBROnto specifies a modelling framework to describe reusable CBR Problem Solving Methods based on the CBR tasks they solve. This paper describes CBROnto’s main ideas and exemplifies them withan application to generate Spanishpoetry versions of texts provided by the user.

The Grid: Stronger, Bigger, Smarter? Presenting a conceptual framework of power system resilience

Interactive storytelling is a rapidly emerging field that tries to reconcile story-like experiences with user control. These forces oppose each other, as story implies predetermination and author intent, and interactivity implies freedom and variability. This paper focuses on unscripted (emergent) narrative and addresses the authoring problem resulting from bringing story development into free form interaction. It discusses the possibility of writing story pieces as input knowledge, portraying both believable character behaviour and interesting story situations. It also discusses how such input knowledge can be a source of inspiration for agents in an emergent narrative simulation to improve its potential for story development