Personality and Emotion for Virtual Characters in Strong-Story Narrative Planning

Interactive virtual worlds provide an immersive and effective environment for training, education, and entertainment purposes. Virtual characters are an essential part of every interactive narrative. The interaction of rich virtual characters can produce interesting narratives and enhance user experience in virtual environments. I propose models of personality and emotion that are highly domain independent and integrate those models into multi-agent strong-story narrative planning systems. I demonstrate the value of the strong-story properties of the model by generating story conflicts intelligently. My models of emotion and personality enable the narrative generation system to create more opportunities for players to resolve conflicts using certain behavior types. In doing so, the author can encourage the player to adopt and exhibit those behaviors. I conduct multiple human subject and case studies to evaluate these models and show that they enable generating a larger number of stories and character behavior that is preferred and more believable to a human audience

Player Modeling

Player modeling is the study of computational models of players in games. This includes the detection, modeling, prediction and expression of human player characteristics which are manifested through cognitive, affective and behavioral patterns. This chapter introduces a holistic view of player modeling and provides a high level taxonomy and discussion of the key components of a player\u27s model. The discussion focuses on a taxonomy of approaches for constructing a player model, the available types of data for the model\u27s input and a proposed classification for the model\u27s output. The chapter provides also a brief overview of some promising applications and a discussion of the key challenges player modeling is currently facing which are linked to the input, the output and the computational model

An Actor-Centric Approach to Facial Animation Control by Neural Networks For Non-Player Characters in Video Games

Game developers increasingly consider the degree to which character animation emulates facial expressions found in cinema. Employing animators and actors to produce cinematic facial animation by mixing motion capture and hand-crafted animation is labor intensive and therefore expensive. Emotion corpora and neural network controllers have shown promise toward developing autonomous animation that does not rely on motion capture. Previous research and practice in disciplines of Computer Science, Psychology and the Performing Arts have provided frameworks on which to build a workflow toward creating an emotion AI system that can animate the facial mesh of a 3d non-player character deploying a combination of related theories and methods. However, past investigations and their resulting production methods largely ignore the emotion generation systems that have evolved in the performing arts for more than a century. We find very little research that embraces the intellectual process of trained actors as complex collaborators from which to understand and model the training of a neural network for character animation. This investigation demonstrates a workflow design that integrates knowledge from the performing arts and the affective branches of the social and biological sciences. Our workflow begins at the stage of developing and annotating a fictional scenario with actors, to producing a video emotion corpus, to designing training and validating a neural network, to analyzing the emotion data annotation of the corpus and neural network, and finally to determining resemblant behavior of its autonomous animation control of a 3d character facial mesh. The resulting workflow includes a method for the development of a neural network architecture whose initial efficacy as a facial emotion expression simulator has been tested and validated as substantially resemblant to the character behavior developed by a human actor

Player agency in interactive narrative: audience, actor & author

The question motivating this review paper is, how can computer-based interactive narrative be used as a constructivist learn- ing activity? The paper proposes that player agency can be used to link interactive narrative to learner agency in constructivist theory, and to classify approaches to interactive narrative. The traditional question driving research in interactive narrative is, ‘how can an in- teractive narrative deal with a high degree of player agency, while maintaining a coherent and well-formed narrative?’ This question derives from an Aristotelian approach to interactive narrative that, as the question shows, is inherently antagonistic to player agency. Within this approach, player agency must be restricted and manip- ulated to maintain the narrative. Two alternative approaches based on Brecht’s Epic Theatre and Boal’s Theatre of the Oppressed are reviewed. If a Boalian approach to interactive narrative is taken the conflict between narrative and player agency dissolves. The question that emerges from this approach is quite different from the traditional question above, and presents a more useful approach to applying in- teractive narrative as a constructivist learning activity

A Domain-Specific Modeling approach for a simulation-driven validation of gamified learning environments Case study about teaching the mimicry of emotions to children with autism

Game elements are rarely explicit when designing serious games or gamified learning activities. We think that the overall design, including instructional design aspects and gamification elements, should be validate by involved experts in the earlier stage of the general design & develop process. We tackle this challenge by proposing a Domain-specific Modeling orientation to our proposals: a metamodeling formalism to capture the gamified instructional design model, and a specific validation process involving domain experts. The validation includes a static verification , by using this formalism to model concrete learning sessions based on concrete informations from real situations described by experts, and a dynamic verification, by developing a simplified simulator for 'execut-ing' the learning sessions scenarios with experts. This propositions are part of the EmoTED research project about a learning application, the mimicry of emotions, for children with ASD. It aims at reinforce face-to-face teaching sessions with therapists by training sessions at home with the supervision of the children's parents. This case-study will ground our proposals and their experimentations

Piecing Together Performance: Collaborative, Participatory Research-Through-Design for Better Diversity in Games

Digital games are a multi-billion-dollar industry whose production and consumption extend globally. Representation in games is an increasingly important topic. As those who create and consume the medium grow ever more diverse, it is essential that player or user-experience research, usability, and any consideration of how people interface with their technology is exercised through inclusive and intersectional lenses. Previous research has identified how character configuration interfaces preface white-male defaults [39, 40, 67]. This study relies on 1-on-1 play-interviews where diverse participants attempt to create “themselves” in a series of games and on group design activities to explore how participants may envision more inclusive character configuration interface design. Our interview findings describe specific points of tension in the process of creating characters in existing interfaces and the sketches participant-collaborators produced challenge the homogeneity of current interface designs. This project amplifies the perspective of diverse participant-collaborators to provide constructive implications and a series of principles for designing more inclusive character configuration interfaces, which support more diverse stories and gameworlds by reconfiguring the constraints that shape those stories and gameworlds

'Stitched up' in the 'Conversengine': using expressive processing and multimodal languages to create a character-driven interactive digital narrative

My practice-based research, which this thesis supports, explores the question: How can a convincing interactive character, with apparent psychological depth, be modelled in a playable digital narrative that adapts to reader choice? To this end I am building my own platform, the 'Conversengine', for authoring and, in future, publishing and playing text-driven interactive narratives that rely on enactment rather than narration. Currently, the platform consists of the 'Convowriter', the authoring tool, which I am using to develop 'Stitched Up', an interactive psychological thriller. Using the concept of the black box from second-order cybernetics with possible worlds and theory of mind from narratology, I show how combining these theories, mapping one onto another, provides a framework for not only thinking about the character-driven interactive narrative, but also a methodology for authoring one, in both natural language and computer code, and designing its richly responsive visual interface. This incorporates a unique emotional data visualisation system ('emoviz') to dynamically represent interactive fictional characters. This system is built upon the Pleasure-Arousal-Dominance Emotional State Model (Russell and Mehrabian, 1977) and informed by existing psychological research into colour, shape and motion. I contend that abstract visualisations, coupled with the characters' text-based thoughts and/or speech, can eloquently express convincing mental and emotional behaviour. This provides the feedback in my cybernetic 'steering-a-course' game engine, which, whilst maintaining narrative coherence, allows the reader-player to steer their own course through the narrative. Creating an interactive narrative of this kind, which simulates psychological rather than physical action, requires a different approach to game writing, development and design. In part two of this thesis, I explore how the distinction between story and narrative discourse has practical implications for the creation of interactive digital narratives. I discuss how using existing game engines and tools can be limiting, and how this led to building my own interactive narrative engine with its own expressive domain-specific language. I show how the combined features of the 'Conversengine' offer a new way of representing complex interactive characters with psychological depth