Plan-based narrative generation with coordinated subplots

Despite recent progress in plan-based narrative generation, one major limitation is that systems tend to produce a single plotline whose progression entirely determines the narrative experience. However, for certain narrative genres such as serial dramas and soaps, multiple interleaved subplots are expected by the audience, as this tends to be the norm in real-world, human-authored narratives. Current narrative generation techniques have overlooked this important requirement, something which could improve the perceived quality of generated stories. To this end, we have developed a flexible plan-based approach to multiplot narrative generation, that successfully generates narratives conforming to different subplot profiles, in terms of the number of subplots interleaved and the relative time spent on each presentation. We have identified specific challenges such as: distribution of virtual characters across subplots; length of each subplot presentation; and transitioning between subplots. In this paper, we overview this approach and describe its operation in a prototype Interactive Storytelling (IS) System set in the serial drama genre. Results of experiments with the system demonstrate its usability. Furthermore, results of a user study highlight the potential of the approach, with clear user preference for presentations that feature interleaved multiple subplots

Emergent situations in interactive storytelling

Interactive storytelling can either be based on explicit plot representations or on the autonomous behaviour of artificial characters. In such a character-based approach, the dynamic interaction between characters generates the actual plot from a generic storyline. Characters' behaviours are implemented through real-time search-based planning techniques. However, the top-down planning systems that control artificial actors need to be complemented with appropriate mechanisms dealing with emerging ("bottom-up") situations of narrative relevance. After discussing the determinants of plot variability and the mechanisms that account for the emergence of narrative situations, we introduce additional mechanisms for coping with these situations. Thes

Character-Based Interactive Storytelling

is a privileged application of intelligent virtual-actors technology. The authors introduce their character-based interactive storytelling prototype that uses Hierarchical Task Network planning techniques, which support story generation and anytime user intervention

BCI Control of Heuristic Search Algorithms

The ability to develop Brain-Computer Interfaces (BCI) to Intelligent Systems would offer new perspectives in terms of human supervision of complex Artificial Intelligence (AI) systems, as well as supporting new types of applications. In this article, we introduce a basic mechanism for the control of heuristic search through fNIRS-based BCI. The rationale is that heuristic search is not only a basic AI mechanism but also one still at the heart of many different AI systems. We investigate how users’ mental disposition can be harnessed to influence the performance of heuristic search algorithm through a mechanism of precision-complexity exchange. From a system perspective, we use weighted variants of the A? algorithm which have an ability to provide faster, albeit suboptimal solutions. We use recent results in affective BCI to capture a BCI signal, which is indicative of a compatible mental disposition in the user. It has been established that Prefrontal Cortex (PFC) asymmetry is strongly correlated to motivational dispositions and results anticipation, such as approach or even risk-taking, and that this asymmetry is amenable to Neurofeedback (NF) control. Since PFC asymmetry is accessible through fNIRS, we designed a BCI paradigm in which users vary their PFC asymmetry through NF during heuristic search tasks, resulting in faster solutions. This is achieved through mapping the PFC asymmetry value onto the dynamic weighting parameter of the weighted A* (WA*) algorithm. We illustrate this approach through two different experiments, one based on solving 8-puzzle configurations, and the other on path planning. In both experiments, subjects were able to speed up the computation of a solution through a reduction of search space in WA?. Our results establish the ability of subjects to intervene in heuristic search progression, with effects which are commensurate to their control of PFC asymmetry: this opens the way to new mechanisms for the implementation of hybrid cognitive systems

Sex, lies, and video games::An interactive storytelling prototype

The authors describe a first prototype of an Interactive Storytelling system, whose objective is to allow user intervention within a pre-defined storyline. The system is character-based rather than plot-based, each character’s role being dynamically computed using HTN planning. The interaction between characters creates various instantiations of the baseline narrative, with which the user can interfere at any time. After introducing the basic AI techniques used in the prototype, the authors discuss the modalities of user intervention and present an example story produced by the system

Revisiting Character-Based Affective Storytelling under a Narrative BDI Framework

Belief-Desire-Intention (BDI) is a well-known cognitive theory, especially in the field of Software Agents. Modelling characters using software agents has been proven to be a suitable approach for obtaining emergent and autonomous behaviours in Interactive Storytelling. In this paper it is claimed that an effective extension of previous models to the BDI framework is useful for designing intelligent characters. An example shows how internal thoughts and motivations of Madame Bovary’s main characters can be more naturally formalised as a cognitive side of the story. A narrative reformulation of BDI theory is needed to avoid the implicit complexity of other proposals