Story plot generation based on CBR

Gervás, Pablo; Dí­az-Agudo, Belén; Peinado, Federico Lara; Hervás, Raquel

doi:10.1016/j.knosys.2004.10.011

Cited by 130 publications

(77 citation statements)

References 7 publications

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“…Planning a series of actions for solving a problem is a type of narrative or story generation. Actually, AI techniques of problem solving such as goal-based planning and case-based reasoning are among the major approaches to computational narrative generation [14], [15], [22], [23]. In the context of problem solving, computational narrative ability will be a basis for creating a narrative as a solution, proposing it to humans, and improving it through interaction with humans.…”

Section: B Cooperative Problem Solvingmentioning

confidence: 99%

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Exploratory Approach to the Computational Modeling of Narrative Ability for Artificial Intelligence

Akimoto¹

2016

IJKE

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Abstract-Narrative ability is an essential element of human intelligence from the perspectives of both psychology and artificial intelligence (AI). It includes many intellectual functions: narrative generation, narrative understanding or interpretation, narrative-mediated communication, and the manipulation of narrativity-based knowledge. The computational modeling of narrative ability is a critical problem in the development of human-like AI agents and user-friendly intelligent information systems. However, implementing this model involves many difficult challenges owing to the structural and phenomenal complexity of narratives. The broader purpose of this study is to develop a computational model of narrative ability from an AI perspective. In this study, we explore the formulation of a conceptual framework of computational narrative ability including a narrativity-based knowledge model and operational modules for this knowledge model. Index Terms-Artificial intelligence, computational narrative ability, narrative agent, story-form knowledge.

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Section: B Cooperative Problem Solvingmentioning

confidence: 99%

“…The ability to produce future stories is a sign of intelligence relevant to problem solving by using techniques such as goal-based planning and case-based reasoning. The techniques of planning and case-based reasoning are also applied to narrative generation systems [14], [15], [22], [23].…”

Section: ) Experience-based Storiesmentioning

confidence: 99%

Exploratory Approach to the Computational Modeling of Narrative Ability for Artificial Intelligence

Akimoto¹

2016

IJKE

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“…Concerned with building this kind of narrative agents, the area has investigated various directions including: interactive drama or storytelling (Mateas 1999;Mateas and Stern 2002;Stern 2003;Cavazza, Martin, Charles, Mead, and Marichal 2003;Magerko 2005;Aylett, Figueiredo, Louchart, Dias, and Paiva 2006;Riedl and Stern 2006;Ram, Ontãnón and Mehta 2007), event structures and organisations for storytelling (Meehan 1976;Lebowitz 1985;Pérez y Pérez and Sharples 2001;Riedl 2004;Gervás, Díaz-Agudo, Peinado and Hervás 2005;Nakasone and Ishizuka 2006;Ho, Dias, Figueiredo and Paiva 2007), social and narrative understanding (Cullingford 1981;Moorman and Ram 1993;Datenhahn and Nehaniv 1998;Dautenhahn 2002Dautenhahn , 2003Mueller 2004), autonomous camera agents (Hornung, Lakemeyer, and Trogemann 2003), narrative in virtual environments (Aylett 1999), etc. Researchers have brought forward fruitful ideas to enhance both storytelling abilities and believability of narrative agents interacting with human users.…”

Section: Related Workmentioning

confidence: 99%

Computational memory architectures for autobiographic agents interacting in a complex virtual environment: a working model

Dautenhahn

Nehaniv

2008

Connection Science

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In this paper, we discuss the concept of autobiographic agent and how memory may extend an agent's temporal horizon and increase its adaptability. These concepts are applied to an implementation of a scenario where agents are interacting in a complex virtual artificial life environment. We present computational memory architectures for autobiographic virtual agents that enable agents to retrieve meaningful information from their dynamic memories which increases their adaptation and survival in the environment. The design of the memory architectures, the agents, and the virtual environment are described in detail. Next, a series of experimental studies and their results are presented which show the adaptive advantage of autobiographic memory, i.e. from remembering significant experiences. Also, in a multi-agent scenario where agents can communicate via stories based on their autobiographic memory, it is found that new adaptive behaviours can emerge from an individual's reinterpretation of experiences received from other agents whereby higher communication frequency yields better group performance. An interface is described that visualises the memory contents of an agent. From an observer perspective, the agents' behaviours can be understood as individually structured, and temporally grounded, and, with the communication of experience, can be seen to rely on emergent mixed narrative reconstructions combining the experiences of several agents. This research leads to insights into how bottom-up story-telling and autobiographic reconstruction in autonomous, adaptive agents allow temporally grounded behaviour to emerge. The article concludes with a discussion of possible implications of this research direction for future autobiographic, narrative agents.

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“…Up till now, CBR is used only sporadically in interactive storytelling or story generation projects. The interactive storytelling system OPIATE uses CBR to achieve morphological plot variation [3], similar to [4]. MINSTREL [14] is model of story generation using CBR to modify and recombine predefined episodic knowledge structures to construct stories.…”

Section: Narrative Inspiration From Example Story Piecesmentioning

confidence: 99%

Using Narrative Cases to Author Interactive Story Content

Swartjes

2007

Entertainment Computing – ICEC 2007

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Abstract. 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.

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Story plot generation based on CBR

Cited by 130 publications

References 7 publications

Exploratory Approach to the Computational Modeling of Narrative Ability for Artificial Intelligence

Exploratory Approach to the Computational Modeling of Narrative Ability for Artificial Intelligence

Computational memory architectures for autobiographic agents interacting in a complex virtual environment: a working model

Using Narrative Cases to Author Interactive Story Content

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