Modulating the performance of VR navigation tasks using different methods of presenting visual information

Spatial navigation is an essential ability in our daily lives that we use to move through different locations. In Virtual Reality (VR), the environments that users navigate may be large and similar to real world places. It is usually desirable to guide users in order to prevent them from getting lost and to make it easier for them to reach the goal or discover important spots in the environment. However, doing so in a way that the guidance is not intrusive, breaking the immersion and sense of presence, nor too hard to notice, therefore not being useful, can be a challenge. In this work we conducted an experiment in which we adapted a probabilistic learning paradigm: the Weather Prediction task to spatial navigation in VR. Subjects navigated one of the two versions of procedurally generated T-junction mazes in Virtual Reality. In one version, the environment contained visual cues in the form of street signs whose presence predicted the correct turning direction. In the other version the cues were present, but were not predictive. Results showed that when subjects navigated the mazes with the predictive cues they made less mistakes, and therefore the cues helped them navigate the environments. A comparison with previous Neuroscience literature revealed that the strategies used by subjects to solve the task were different than in the original 2D experiment. This work is intended to be used as a basis to further improve spatial navigation in VR with more immersive and implicit methods, and as another example of how the Cognitive Neurosicence and Virtual Reality research fields can greatly benefit each other

Implementation and playtesting for a world adventure game’s procedural content generation system

This paper presents an experimental methodology of procedural content generation (PCG) for natural environments focusing on game design and visualization. This approach allows us to define a set of instructions to shape the content generation to meet the requirements of game design and level design teams. For the validation process, we have discussed and analyzed a playtesting session.info:eu-repo/semantics/submittedVersio

Ludotopia

Where do computer games »happen«? The articles collected in this pioneering volume explore the categories of »space«, »place« and »territory« featuring in most general theories of space to lay the groundwork for the study of spatiality in games. Shifting the focus away from earlier debates on, e.g., the narrative nature of games, this collection proposes, instead, that thorough attention be given to the tension between experienced spaces and narrated places as well as to the mapping of both of these

Ludotopia

Where do computer games »happen«? The articles collected in this pioneering volume explore the categories of »space«, »place« and »territory« featuring in most general theories of space to lay the groundwork for the study of spatiality in games. Shifting the focus away from earlier debates on, e.g., the narrative nature of games, this collection proposes, instead, that thorough attention be given to the tension between experienced spaces and narrated places as well as to the mapping of both of these

GIVE-ME: Gamification In Virtual Environments for Multimodal Evaluation - A Framework

In the last few decades, a variety of assistive technologies (AT) have been developed to improve the quality of life of visually impaired people. These include providing an independent means of travel and thus better access to education and places of work. There is, however, no metric for comparing and benchmarking these technologies, especially multimodal systems. In this dissertation, we propose GIVE-ME: Gamification In Virtual Environments for Multimodal Evaluation, a framework which allows for developers and consumers to assess their technologies in a functional and objective manner. This framework is based on three foundations: multimodality, gamification, and virtual reality. It facilitates fuller and more controlled data collection, rapid prototyping and testing of multimodal ATs, benchmarking heterogeneous ATs, and conversion of these evaluation tools into simulation or training tools. Our contributions include: (1) a unified evaluation framework: via developing an evaluative approach for multimodal visual ATs; (2) a sustainable evaluation: by employing virtual environments and gamification techniques to create engaging games for users, while collecting experimental data for analysis; (3) a novel psychophysics evaluation: enabling researchers to conduct psychophysics evaluation despite the experiment being a navigational task; and (4) a novel collaborative environment: enabling developers to rapid prototype and test their ATs with users in an early stakeholder involvement that fosters communication between developers and users. This dissertation first provides a background in assistive technologies and motivation for the framework. This is followed by detailed description of the GIVE-ME Framework, with particular attention to its user interfaces, foundations, and components. Then four applications are presented that describe how the framework is applied. Results and discussions are also presented for each application. Finally, both conclusions and a few directions for future work are presented in the last chapter

Terrain generation algorithms

Procedural terrain generation has become common in games as a whole and in indie games in particular. With procedural terrain generation developers can relatively easily create static or dynamically expanding game areas. Also it is more cost effective since large part of manual work can be automated which traditional game areas would require. Goal of this thesis is to introduce and evaluate different algorithms that are used or have potential use cases in terrain generation. Such algorithms as various noise functions, which are widely used in the realm of terrain generation, a number of dungeon algorithms, which use variety of methods to generate the dungeon, fractal algorithm, and volumetric terrain generation algorithm which uses a combination of noise and fractal algorithms. Algorithms and techniques will be searched from various scientific articles and literary sources. Metrics used for terrain generation algorithm evaluation will also be introduced, and algorithms in this thesis will be evaluated using these metrics. During evaluation it was noticed that the evaluated noise functions are generally capable of runtime terrain generation, but are lacking in customization and control since parameters are usually related to the algorithm rather than the resulting terrain. Albeit these shortcomings both Perlin and Simplex noise stand out for their ability to generate good quality terrains. On the other hand most of the evaluated dungeon generation algorithms are incapable of generating terrain during runtime with few exceptions. Also guaranteeing connectivity of rooms or areas in dungeon can be challenge in some algorithms. The introduced fractal algorithm is metrics wise similar to Perlin and Simplex noise even though it uses completely different method to generate the terrain. The volumetric terrain generation algorithm is the only algorithm capable of generating volumetric terrain and its high level of parametrization and customization is its strongest quality

Immersion design and worldbuilding for the development of introspective and alterbiographical narratives in First Person Exploration video games

Treball final de Grau en Disseny i Desenvolupament de Videojocs. Codi: VJ1241. Curs acadèmic: 2019/2020The hereby document represents the Final Report for a bachelor's thesis on Video Game Design and Development. The following work consists of the design and development of Oceans of Reflection, a video game based on introspective and alterbiographical narratives that allows the player to approach their own being through mechanics and environment. More specifically, the aim is to enable the player to construct the narrative jointly with us, the developers, moving away from traditional narratives and adapting the experience for each of the users in such a way that it is completely personalized. The video game could be classified in the First Person Exploration and Puzzle Game genre and it will be developed in Unity 3D for PC using, inter alia, technologies such as Unity Shader Graph and voice recognition

Amergent Music: behavior and becoming in technoetic & media arts

Merged with duplicate records 10026.1/1082 and 10026.1/2612 on 15.02.2017 by CS (TIS)Technoetic and media arts are environments of mediated interaction and emergence, where meaning is negotiated by individuals through a personal examination and experience—or becoming—within the mediated space. This thesis examines these environments from a musical perspective and considers how sound functions as an analog to this becoming. Five distinct, original musical works explore the possibilities as to how the emergent dynamics of mediated, interactive exchange can be leveraged towards the construction of musical sound. In the context of this research, becoming can be understood relative to Henri Bergson’s description of the appearance of reality—something that is making or unmaking but is never made. Music conceived of a linear model is essentially fixed in time. It is unable to recognize or respond to the becoming of interactive exchange, which is marked by frequent and unpredictable transformation. This research abandons linear musical approaches and looks to generative music as a way to reconcile the dynamics of mediated interaction with a musical listening experience. The specifics of this relationship are conceptualized in the structaural coupling model, which borrows from Maturana & Varela’s “structural coupling.” The person interacting and the generative musical system are compared to autopoietic unities, with each responding to mutual perturbations while maintaining independence and autonomy. Musical autonomy is sustained through generative techniques and organized within a psychogeographical framework. In the way that cities invite use and communicate boundaries, the individual sounds of a musical work create an aural context that is legible to the listener, rendering the consequences or implications of any choice audible. This arrangement of sound, as it relates to human presence in a technoetic environment, challenges many existing assumptions, including the idea “the sound changes.” Change can be viewed as a movement predicated by behavior. Amergent music is brought forth through kinds of change or sonic movement more robustly explored as a dimension of musical behavior. Listeners hear change, but it is the result of behavior that arises from within an autonomous musical system relative to the perturbations sensed within its environment. Amergence propagates through the effects of emergent dynamics coupled to the affective experience of continuous sonic transformation.Rutland Port Authoritie

On Realization of Intelligent Decision-Making in the Real World: A Foundation Decision Model Perspective

Our situated environment is full of uncertainty and highly dynamic, thus hindering the widespread adoption of machine-led Intelligent Decision-Making (IDM) in real world scenarios. This means IDM should have the capability of continuously learning new skills and efficiently generalizing across wider applications. IDM benefits from any new approaches and theoretical breakthroughs that exhibit Artificial General Intelligence (AGI) breaking the barriers between tasks and applications. Recent research has well-examined neural architecture, Transformer, as a backbone foundation model and its generalization to various tasks, including computer vision, natural language processing, and reinforcement learning. We therefore argue that a foundation decision model (FDM) can be established by formulating various decision-making tasks as a sequence decoding task using the Transformer architecture; this would be a promising solution to advance the applications of IDM in more complex real world tasks. In this paper, we elaborate on how a foundation decision model improves the efficiency and generalization of IDM. We also discuss potential applications of a FDM in multi-agent game AI, production scheduling, and robotics tasks. Finally, through a case study, we demonstrate our realization of the FDM, DigitalBrain (DB1) with 1.2 billion parameters, which achieves human-level performance over 453 tasks, including text generation, images caption, video games playing, robotic control, and traveling salesman problems. As a foundation decision model, DB1 would be a baby step towards more autonomous and efficient real world IDM applications.Comment: 26 pages, 4 figure

Attributed Intelligence

Human beings quickly and confidently attribute more or less intelligence to one another. What is meant by intelligence when they do so? And what are the surface features of human behaviour that determine their judgements? Because the judges of success or failure in the quest for `artificial intelligence' will be human, the answers to such questions are an essential part of cognitive science. This thesis studies such questions in the context of a maze world, complex enough to require non-trivial answers, and simple enough to analyse the answers in term of decision-making algorithms. According to Theory-theory, humans comprehend the actions of themselves and of others in terms of beliefs, desires and goals, following rational principles of utility. If so, attributing intelligence may result from an evaluation the agent's efficiency -- how closely its behaviour approximates the expected rational course of action. Alternatively, attributed intelligence could result from observing outcomes: billionaires and presidents are, by definition, intelligent. I applied Bayesian models of planning under uncertainty to data from five behavioural experiments. The results show that while most humans attribute intelligence to efficiency, a minority attributes intelligence to outcome. Understanding of differences in attributed intelligence comes from a study how people plan. Most participants can optimally plan 1-5 decisions in advance. Individually they vary in sensitivity to decision value and in planning depth. Comparing planning performance and attributed intelligence shows that observers' ability to attribute intelligence depends on their ability to plan. People attribute intelligence to efficiency in proportion to their planning ability. The less skilled planners are more likely to attribute intelligence to outcome. Moreover, model-based metrics of planning performance correlate with independent measures of cognitive performance, such as the Cognitive Reflection Test and pupil size. Eyetracking analysis of spatial planning in real-time shows that participants who score highly on independent measures of cognitive ability also plan further ahead. Taken together, these results converge on a theory of attributed intelligence as an evaluation of how efficiently an agent plans, such that depends on the observer's cognitive abilities to carry out the evaluation