Virtual environments promoting interaction

Virtual reality (VR) has been widely researched in the academic environment and is now breaking into the industry. Regular companies do not have access to this technology as a collaboration tool because these solutions usually require specific devices that are not at hand of the common user in offices. There are other collaboration platforms based on video, speech and text, but VR allows users to share the same 3D space. In this 3D space there can be added functionalities or information that in a real-world environment would not be possible, something intrinsic to VR. This dissertation has produced a 3D framework that promotes nonverbal communication. It plays a fundamental role on human interaction and is mostly based on emotion. In the academia, confusion is known to influence learning gains if it is properly managed. We designed a study to evaluate how lexical, syntactic and n-gram features influence perceived confusion and found results (not statistically significant) that point that it is possible to build a machine learning model that can predict the level of confusion based on these features. This model was used to manipulate the script of a given presentation, and user feedback shows a trend that by manipulating these features and theoretically lowering the level of confusion on text not only drops the reported confusion, as it also increases reported sense of presence. Another contribution of this dissertation comes from the intrinsic features of a 3D environment where one can carry actions that in a real world are not possible. We designed an automatic adaption lighting system that reacts to the perceived user’s engagement. This hypothesis was partially refused as the results go against what we hypothesized but do not have statistical significance. Three lines of research may stem from this dissertation. First, there can be more complex features to train the machine learning model such as syntax trees. Also, on an Intelligent Tutoring System this could adjust the avatar’s speech in real-time if fed by a real-time confusion detector. When going for a social scenario, the set of basic emotions is well-adjusted and can enrich them. Facial emotion recognition can extend this effect to the avatar’s body to fuel this synchronization and increase the sense of presence. Finally, we based this dissertation on the premise of using ubiquitous devices, but with the rapid evolution of technology we should consider that new devices will be present on offices. This opens new possibilities for other modalities.A Realidade Virtual (RV) tem sido alvo de investigação extensa na academia e tem vindo a entrar na indústria. Empresas comuns não têm acesso a esta tecnologia como uma ferramenta de colaboração porque estas soluções necessitam de dispositivos específicos que não estão disponíveis para o utilizador comum em escritório. Existem outras plataformas de colaboração baseadas em vídeo, voz e texto, mas a RV permite partilhar o mesmo espaço 3D. Neste espaço podem existir funcionalidades ou informação adicionais que no mundo real não seria possível, algo intrínseco à RV. Esta dissertação produziu uma framework 3D que promove a comunicação não-verbal que tem um papel fundamental na interação humana e é principalmente baseada em emoção. Na academia é sabido que a confusão influencia os ganhos na aprendizagem quando gerida adequadamente. Desenhámos um estudo para avaliar como as características lexicais, sintáticas e n-gramas influenciam a confusão percecionada. Construímos e testámos um modelo de aprendizagem automática que prevê o nível de confusão baseado nestas características, produzindo resultados não estatisticamente significativos que suportam esta hipótese. Este modelo foi usado para manipular o texto de uma apresentação e o feedback dos utilizadores demonstra uma tendência na diminuição do nível de confusão reportada no texto e aumento da sensação de presença. Outra contribuição vem das características intrínsecas de um ambiente 3D onde se podem executar ações que no mundo real não seriam possíveis. Desenhámos um sistema automático de iluminação adaptativa que reage ao engagement percecionado do utilizador. Os resultados não suportam o que hipotetizámos mas não têm significância estatística, pelo que esta hipótese foi parcialmente rejeitada. Três linhas de investigação podem provir desta dissertação. Primeiro, criar características mais complexas para treinar o modelo de aprendizagem, tais como árvores de sintaxe. Além disso, num Intelligent Tutoring System este modelo poderá ajustar o discurso do avatar em tempo real, alimentado por um detetor de confusão. As emoções básicas ajustam-se a um cenário social e podem enriquecê-lo. A emoção expressada facialmente pode estender este efeito ao corpo do avatar para alimentar o sincronismo social e aumentar a sensação de presença. Finalmente, baseámo-nos em dispositivos ubíquos, mas com a rápida evolução da tecnologia, podemos considerar que novos dispositivos irão estar presentes em escritórios. Isto abre possibilidades para novas modalidades

General general game AI

Arguably the grand goal of artificial intelligence research is to produce machines with general intelligence: the capacity to solve multiple problems, not just one. Artificial intelligence (AI) has investigated the general intelligence capacity of machines within the domain of games more than any other domain given the ideal properties of games for that purpose: controlled yet interesting and computationally hard problems. This line of research, however, has so far focused solely on one specific way of which intelligence can be applied to games: playing them. In this paper, we build on the general game-playing paradigm and expand it to cater for all core AI tasks within a game design process. That includes general player experience and behavior modeling, general non-player character behavior, general AI-assisted tools, general level generation and complete game generation. The new scope for general general game AI beyond game-playing broadens the applicability and capacity of AI algorithms and our understanding of intelligence as tested in a creative domain that interweaves problem solving, art, and engineering.peer-reviewe

Videogame focused on the autism spectrum disorder among children and their understanding of emotions

Treball final de Grau en Disseny i Desenvolupament de Videojocs. Codi: VJ1241. Curs acadèmic: 2017/2018This document is a memory for my final project of the degree on Design and Development of Videogames. I will explain the entire development process. from the idea to the final testing. It consists in a videogame, a graphic adventure, focused on showing children with autism spectrum disorder how to recognise and understand a range of emotions such as happiness, sadness, anger or fear. In this adventure, the player starts a journey, where each different place we come by will be based on one of those basic feelings. I will initially focus on a fully functional game with at least two or three emotions/villages, and then I will expand it. Moreover, it will include some narrative mechanics in order to increase the playability and increase the number of narrative lines. This game has been developed with Unity3D for computer, and will be playable in English and Spanish. Last but not least, this project is supported on existing scientific work (links added at the end). For instance, I will be using one of the methods described in [2] to visually express emotions, which consists on associating each one to a specific non-verbal code, like colors or symbols, that will be unique for each village. Last but not least, I got a lot of help from the Autism center of Castellón, in regard to collect information and being with children in their activities

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

Agents for educational games and simulations

This book consists mainly of revised papers that were presented at the Agents for Educational Games and Simulation (AEGS) workshop held on May 2, 2011, as part of the Autonomous Agents and MultiAgent Systems (AAMAS) conference in Taipei, Taiwan. The 12 full papers presented were carefully reviewed and selected from various submissions. The papers are organized topical sections on middleware applications, dialogues and learning, adaption and convergence, and agent applications

Procedural and semantic modeling of virtual environments for serious games development

International audienceVirtual environments are useful tools for visualization, discovery as well as training. In serious or learning games contexts, 3D graphical worlds, interaction, navigation and immersion capabilities are needed to propel narration and emotion. Furthermore, they are key elements to materialize pedagogical content and to support knowledge transfer. Semantic modeling, serious game classification and gameplay component identification allow generating serious game scenarios linked to the 3D world modeling and interaction or animation capabilities

Videogame-based learning: a comparison of direct and indirect effects across outcomes

2017 Summer.Includes bibliographical references.Recent years have shown a rise in the application of serious games used by organizations to help trainees learn and practice job related skills (Muntean, 2011). Some sources have projected a continued growth in the development and application of video games for novel purposes (Sanders, 2015). Despite the increasing use of video games for workplace training, there is limited research evidence to justify the use of video games for learning. Additionally, this research has generated mixed results on the utility of serious games (Guillen-Nieto & Aleson-Carbonell, 2012). One contribution of this study is a review of the research literature to understand why videogame-based learning research is producing inconsistent results. From this review, I present several current challenges in the research literature that may be contributing to these inconsistencies; distinguishing videogames from similar training media, identifying game characteristics, exploring the possible mechanisms in the training experience, differentiating training outcomes, and making accurate implications for research. The purpose of this study is to design and test a new approach to game-based learning research that would explore the context in which games are effective learning tools. This study tested and expanded the model from Garris et al.'s (2002) game-based learning I-P-O model to determine the extent to which one game characteristic (i.e., human interaction) influences two training outcomes (i.e., declarative knowledge and affective states), as well as the possible mechanisms through which this occurs. The present study found that active learning is a mechanism through which human interaction influences both declarative knowledge and affective states. Although the effect size was large for affective states, it was small for declarative knowledge. The mediating effect of active learning was greater for the relationship between human interaction and affective states than for the relationship between human interaction and declarative knowledge. I also found that perceived value mediates the relationship between human interaction and affective states