Game Engine Solutions

The rapid development of hardware and system platforms provides a favorable foundation for game development. A game engine overview is introduced first. Then, key features and available solutions of game engines are discussed. Typical products of game engines are shown and evaluated. Finally, we summarize our findings

Cognitive fatigue: Exploring the relationship between the fatigue effect and action video-game experience

the effects of cognitive fatigue. Despite this, there remain advantages to regularly playing action video games. In Study 1, VGPs were significantly better at multitasking on the MATB-II compared to the NVGPs. Further, VGPs also demonstrated superior multitasking when driving, as they made significantly fewer traffic violations compared to NVGPs when not fatigued. VGPs demonstrated eye-movements similar to those of expert drivers; however, this did not result in any difference in performance between the two groups. There was also some evidence of a positive effect of video game training, although there was no advantage of one training technique over the other. In Study 2, participants experienced the effects of cognitive fatigue to a lesser extent after video game training than compared to before training. Further, there was a significant improvement in multitasking performance after video game training, though as participants continued improving even at the three-month follow up test, it is unknown whether this was due to the video game training or due to practice effects on the MATB-II. Overall, despite improvements in sustained and divided attention performance from regular action video game playing or training, VGPs and trained-NVGPs are just as susceptible to the effects of cognitive fatigue as NVGPs

Development of a Physics-Aware Dead Reckoning Mechanism for Distributed Interactive Applications

Distributed Interactive Applications (DIAs) are a class of software that allow geographically remote users to interact within a shared virtual environment. Many DIAs seek to present a rich and realistic virtual world to users, both on a visual and behavioural level. A relatively recent addition to virtual environments (both distributed and single user) to achieve the latter has been the simulation of realistic physical phenomena between objects in the environment. However, the application of physics simulation to virtual environments in DIAs currently lags that of single user environments. This is primarily due to the unavailability of entity state update mechanisms which can maintain consistency in such physics-rich environments. The difference is particularly evident in applications built on a peer-to-peer architecture, as a lack of a single authority presents additional challenges in synchronising the state of shared objects while also presenting a responsive simulation. This thesis proposes a novel state maintenance mechanism for physics-rich environments in peer-to-peer DIAs composed of two parts: a dynamic authority scheme for shared objects, and a physics-aware dead reckoning model with an adaptive error threshold. The first part is intended to place a bound on the overall inconsistency present in shared objects, while the second is implemented to minimise the instantaneous inconsistency during users’ interactions with shared objects. A testbed application is also described, which is used to validate the performance of the proposed mechanism. The state maintenance mechanism is implemented for a single type of physicsaware application, and demonstrates a marked improvement in consistency for that application. However, several flexible terms are described in its implementation, as well as their potential relevance to alternative applications. Finally, it should be noted that the physics-aware dead reckoning model does not depend on the authority scheme, and can therefore be employed with alternative authority scheme

Proceedings of the SAB'06 Workshop on Adaptive Approaches for Optimizing Player Satisfaction in Computer and Physical Games

These proceedings contain the papers presented at the Workshop on Adaptive approaches for Optimizing Player Satisfaction in Computer and Physical Games held at the Ninth international conference on the Simulation of Adaptive Behavior (SAB’06): From Animals to Animats 9 in Rome, Italy on 1 October 2006. We were motivated by the current state-of-the-art in intelligent game design using adaptive approaches. Artificial Intelligence (AI) techniques are mainly focused on generating human-like and intelligent character behaviors. Meanwhile there is generally little further analysis of whether these behaviors contribute to the satisfaction of the player. The implicit hypothesis motivating this research is that intelligent opponent behaviors enable the player to gain more satisfaction from the game. This hypothesis may well be true; however, since no notion of entertainment or enjoyment is explicitly defined, there is therefore little evidence that a specific character behavior generates enjoyable games. Our objective for holding this workshop was to encourage the study, development, integration, and evaluation of adaptive methodologies based on richer forms of humanmachine interaction for augmenting gameplay experiences for the player. We wanted to encourage a dialogue among researchers in AI, human-computer interaction and psychology disciplines who investigate dissimilar methodologies for improving gameplay experiences. We expected that this workshop would yield an understanding of state-ofthe- art approaches for capturing and augmenting player satisfaction in interactive systems such as computer games. Our invited speaker was Hakon Steinø, Technical Producer of IO-Interactive, who discussed applied AI research at IO-Interactive, portrayed the future trends of AI in computer game industry and debated the use of academic-oriented methodologies for augmenting player satisfaction. The sessions of presentations and discussions where classified into three themes: Adaptive Learning, Examples of Adaptive Games and Player Modeling. The Workshop Committee did a great job in providing suggestions and informative reviews for the submissions; thank you! This workshop was in part supported by the Danish National Research Council (project no: 274-05-0511). Finally, thanks to all the participants; we hope you found this to be useful!peer-reviewe

Techno-historical limits of the interface: the performance of interactive narrative experiences

This thesis takes the position that current analyses of digitally mediated interactive experiences that include narrative elements often lack adequate consideration of the technical and historical contexts of their production.From this position, this thesis asks the question: how is the reader/player/user's participation in interactive narrative experiences (such as hypertext fiction, interactive fiction, computer games, and electronic art) influenced by the technical and historical limitations of the interface?In order to investigate this question, this thesis develops a single methodology from relevant media and narrative theory, in order to facilitate a comparative analysis of well known exemplars from distinct categories of digitally mediated experiences. These exemplars are the interactive fiction Adventure, the interactive art work Osmose, the hypertext fiction Afternoon, a story, and the computer/video games Myst, Doom, Half Life and Everquest.The main argument of this thesis is that the technical limits of new media experiences cause significant ‘gaps’ in the reader’s experience of them, and that the cause of these gaps is the lack of a dedicated technology for new media, which instead ‘borrows’ technology from other fields. These gaps are overcome by a greater dependence upon the reader’s cognitive abilities than other media forms. This greater dependence can be described as a ‘performance’ by the reader/player/user, utilising Eco’s definition of an ‘open’ work (Eco 21).This thesis further argues that the ‘mimetic’ and ‘immersive’ ambitions of current new media practice can increases these gaps, rather than overcoming them. The thesis also presents the case that these ‘gaps’ are often not caused by technical limits in the present, but are oversights by the author/designers that have arisen as the product of a craft culture that has been subject to significant technical limitations in the past. Compromises that originally existed to overcome technical limits have become conventions of the reader/player/user’s interactive literacy, even though these conventions impinge on the experience, and are no longer necessary because of subsequent technical advances. As a result, current new media users and designers now think of these limitations as natural.This thesis concludes the argument by redefining ‘immersion’ as the investment the reader makes to overcome the gaps in an experience, and suggests that this investment is an important aspect of their performance of the work

Rethinking Social Media and Extremism

Terrorism, global pandemics, climate change, wars and all the major threats of our age have been targets of online extremism. The same social media occupying the heartland of our social world leaves us vulnerable to cybercrime, electoral fraud and the 'fake news' fuelling the rise of far-right violence and hate speech. In the face of widespread calls for action, governments struggle to reform legal and regulatory frameworks designed for an analogue age. And what of our rights as citizens? As politicians and lawyers run to catch up to the future as it disappears over the horizon, who guarantees our right to free speech, to free and fair elections, to play video games, to surf the Net, to believe ‘fake news’? Rethinking Social Media and Extremism offers a broad range of perspectives on violent extremism online and how to stop it. As one major crisis follows another and a global pandemic accelerates our turn to digital technologies, attending to the issues raised in this book becomes ever more urgent

Network Latency in Teleoperation of Connected and Autonomous Vehicles:A Review of Trends, Challenges, and Mitigation Strategies

With remarkable advancements in the development of connected and autonomous vehicles (CAVs), the integration of teleoperation has become crucial for improving safety and operational efficiency. However, teleoperation faces substantial challenges, with network latency being a critical factor influencing its performance. This survey paper explores the impact of network latency along with state-of-the-art mitigation/compensation approaches. It examines cascading effects on teleoperation communication links (i.e., uplink and downlink) and how delays in data transmission affect the real-time perception and decision-making of operators. By elucidating the challenges and available mitigation strategies, the paper offers valuable insights for researchers, engineers, and practitioners working towards the seamless integration of teleoperation in the evolving landscape of CAVs

Imitation learning through games: theory, implementation and evaluation

Despite a history of games-based research, academia has generally regarded commercial games as a distraction from the serious business of AI, rather than as an opportunity to leverage this existing domain to the advancement of our knowledge. Similarly, the computer game industry still relies on techniques that were developed several decades ago, and has shown little interest in adopting more progressive academic approaches. In recent times, however, these attitudes have begun to change; under- and post-graduate games development courses are increasingly common, while the industry itself is slowly but surely beginning to recognise the potential offered by modern machine-learning approaches, though games which actually implement said approaches on more than a token scale remain scarce. One area which has not yet received much attention from either academia or industry is imitation learning, which seeks to expedite the learning process by exploiting data harvested from demonstrations of a given task. While substantial work has been done in developing imitation techniques for humanoid robot movement, there has been very little exploration of the challenges posed by interactive computer games. Given that such games generally encode reasoning and decision-making behaviours which are inherently more complex and potentially more interesting than limb motion data, that they often provide inbuilt facilities for recording human play, that the generation and collection of training samples is therefore far easier than in robotics, and that many games have vast pre-existing libraries of these recorded demonstrations, it is fair to say that computer games represent an extremely fertile domain for imitation learning research. In this thesis, we argue in favour of using modern, commercial computer games to study, model and reproduce humanlike behaviour. We provide an overview of the biological and robotic imitation literature as well as the current status of game AI, highlighting techniques which may be adapted for the purposes of game-based imitation. We then proceed to describe our contributions to the field of imitation learning itself, which encompass three distinct categories: theory, implementation and evaluation. We first describe the development of a fully-featured Java API - the Quake2 Agent Simulation Environment (QASE) - designed to facilitate both research and education in imitation and general machine-learning, using the game Quake 2 as a testbed. We outline our motivation for developing QASE, discussing the shortcomings of existing APIs and the steps which we have taken to circumvent them. We describe QASE’s network layer, which acts as an interface between the local AI routines and the Quake 2 server on which the game environment is maintained, before detailing the API’s agent architecture, which includes an interface to the MatLab programming environment and the ability to parse and analyse full recordings of game sessions. We conclude the chapter with a discussion of QASE’s adoption by numerous universities as both an undergraduate teaching tool and research platform. We then proceed to describe the various imitative mechanisms which we have developed using QASE and its MatLab integration facilities. We first outline a behaviour model based on a well-known psychological model of human planning. Drawing upon previous research, we also identify a set of believability criteria - elements of agent behaviour which are of particular importance in determining the “humanness” of its in-game appearance. We then detail a reinforcement-learning approach to imitating the human player’s navigation of his environment, centred upon his pursuit of items as strategic goals. In the subsequent section, we describe the integration of this strategic system with a Bayesian mechanism for the imitation of tactical and motion-modelling behaviours. Finally, we outline a model for the imitation of reactive combat behaviours; specifically, weapon-selection and aiming. Experiments are presented in each case to demonstrate the imitative mechanisms’ ability to accurately reproduce observed behaviours. Finally, we criticise the lack of any existing methodology to formally gauge the believability of game agents, and observe that the few previous attempts have been extremely ad-hoc and informal. We therefore propose a generalised approach to such testing; the Bot-Oriented Turing Test (BOTT). This takes the form of an anonymous online questionnaire, an accompanying protocol to which examiners should adhere, and the formulation of a believability index which numerically expresses each agent’s humanness as indicated by its observers, weighted by their experience and the accuracy with which the agents were identified. To both validate the survey approach and to determine the efficacy of our imitative models, we present a series of experiments which use the believability test to evaluate our own imitation agents against both human players and traditional artificial bots. We demonstrate that our imitation agents perform substantially better than even a highly-regarded rule-based agent, and indeed approach the believability of actual human players. Some suggestions for future directions in our research, as well as a broader discussion of open questions, conclude this thesis