Optimising Agent Behaviours and Game Parameters to Meet Designer’s Objectives

The game industry is one of the biggest economic sector in the entertainment business whose product rely heavily on the quality of the interactivity to stay relevant. Non-Player Character (NPC) is the main mechanic used for this purpose and it has to be optimised for its designated behaviour. The development process iteratively circulates the results among game designers, game AI developers, and game testers. Automatic optimisation of NPCs to designer’s objective will increase the speed of each iteration, and reduce the overall production time. Previous attempts used entropy evaluation metrics which are difficult to translate the terms to the optimising game and a slight misinterpretation often leads to incorrect measurement. This thesis proposes an alternative method which evaluates generated game data with reference result from the testers. The thesis first presents a reliable way to extract information for NPCs classification called Relative Region Feature (RRF). RRF provides an excellent data compression method, a way to effectively classify, and a way to optimise objective-oriented adaptive NPCs. The formalised optimisation is also proved to work on classifying player skill with the reference hall-of-fame scores. The demonstration are done on the on-line competition version of Ms PacMan. The generated games from participating entries provide challenging optimising problems for various evolutionary optimisers. The thesis developed modified version of CMA-ES and PSO to effectively tackle the problems. It also demonstrates the adaptivity of MCTS NPC which uses the evaluation method. This NPC performs reasonably well given adequate resources and no reference NPC is required

Mixed reality entertainment with wearable computers

Master'sMASTER OF ENGINEERIN

Apraxia World: Deploying a Mobile Game and Automatic Speech Recognition for Independent Child Speech Therapy

Children with speech sound disorders typically improve pronunciation quality by undergoing speech therapy, which must be delivered frequently and with high intensity to be effective. As such, clinic sessions are supplemented with home practice, often under caregiver supervision. However, traditional home practice can grow boring for children due to monotony. Furthermore, practice frequency is limited by caregiver availability, making it difficult for some children to reach therapy dosage. To address these issues, this dissertation presents a novel speech therapy game to increase engagement, and explores automatic pronunciation evaluation techniques to afford children independent practice. Children with speech sound disorders typically improve pronunciation quality by undergoing speech therapy, which must be delivered frequently and with high intensity to be effective. As such, clinic sessions are supplemented with home practice, often under caregiver supervision. However, traditional home practice can grow boring for children due to monotony. Furthermore, practice frequency is limited by caregiver availability, making it difficult for some children to reach therapy dosage. To address these issues, this dissertation presents a novel speech therapy game to increase engagement, and explores automatic pronunciation evaluation techniques to afford children independent practice. The therapy game, called Apraxia World, delivers customizable, repetition-based speech therapy while children play through platformer-style levels using typical on-screen tablet controls; children complete in-game speech exercises to collect assets required to progress through the levels. Additionally, Apraxia World provides pronunciation feedback according to an automated pronunciation evaluation system running locally on the tablet. Apraxia World offers two advantages over current commercial and research speech therapy games; first, the game provides extended gameplay to support long therapy treatments; second, it affords some therapy practice independence via automatic pronunciation evaluation, allowing caregivers to lightly supervise instead of directly administer the practice. Pilot testing indicated that children enjoyed the game-based therapy much more than traditional practice and that the exercises did not interfere with gameplay. During a longitudinal study, children made clinically-significant pronunciation improvements while playing Apraxia World at home. Furthermore, children remained engaged in the game-based therapy over the two-month testing period and some even wanted to continue playing post-study. The second part of the dissertation explores word- and phoneme-level pronunciation verification for child speech therapy applications. Word-level pronunciation verification is accomplished using a child-specific template-matching framework, where an utterance is compared against correctly and incorrectly pronounced examples of the word. This framework identified mispronounced words better than both a standard automated baseline and co-located caregivers. Phoneme-level mispronunciation detection is investigated using a technique from the second-language learning literature: training phoneme-specific classifiers with phonetic posterior features. This method also outperformed the standard baseline, but more significantly, identified mispronunciations better than student clinicians

Evolutionary Design of Game Vehicles and Their Controllers

Procedural content generation (PCG) is a growing field of interest in the domain of computational intelligence as it relates to games. There are ever increasing examples and applications of PCG that have been studied in academic contexts. Player expectations of the amount of content in games increase as computers and video game consoles are capable of using more content, and automation of content creation becomes more desirable. While many means of procedural content generation using some form of search algorithm have been tried and tested, we examine evolutionary algorithms as a means to generate content, where it has not frequently been used before. We examine the generation of vehicles, specifically spaceships, within two dimensional game simulations. These simulations are based upon a simple Newtonian physics system with different physical rules, representing games such as Lunar Lander or Asteroids, and evolve linear vectors of real numbers that act as vehicle genotypes by encoding placement of components to a vehicle point mass, with a form defined by the placement of each component. We use simple 1-ply lookahead controllers, simple rule-based controllers, and MCTS-based controllers as means to test and therefore indirectly guide the evolution of vehicle designs. We are able to demonstrate that evolutionary algorithms can be used to generate effective vehicle designs, suitable for use by the same controller as used for testing, for simple tasks without much issue. We also show that there are some factors of a problem environment that impact the demands and the conditions affecting vehicle design evolution more than others, such as velocity loss factors and the topology of the game world used. It is also evident that the use of different controllers to test vehicles causes different designs to emerge based on the strengths of said controllers

Evaluating the enjoyability of the ghosts in Ms Pac-Man

The video games industry is one of the fastest-growing industries in the world, bolstered by sophisticated technology in gaming consoles and modern trends such as mobile and social gaming. The goal of most video games is to entertain the gamer and in most games this stems from the interaction between the gamer and the non-player characters (NPCs): it is no longer sufficient for a game to be visually appealing but instead, the gamer must be challenged at the right level of difficulty to be engaged by the game. It is thus necessary to develop suitable NPCs that are fun to play against and the realm of computational intelligence offers a variety of techniques to do so. However, the perception of fun is clearly subjective and indeed, difficult to quantify. In this paper we make use of the Ms Pac-Man vs Ghosts gaming competition to gather and analyse data from human gamers regarding their preference of opponent: each gamer plays two games against different ghost teams, indicating their preference at the end. We subsequently use this data to establish which ghost teams are generally preferred and demonstrate that there are measurable differences between these ghost teams. These differences are sufficient to group the ghosts into different categories with a good degree of accuracy. This work is a first step in better understanding the attributes required by NPCs for players to be engaged. © 2012 IEEE

Design models for multimedia learning environments based on interactive drama

Interactive multimedia offers a degree of richness that lies outside the scope of conventional design methods for computer based learning. This research seeks to develop an interdisciplinary approach to design, that recognises the ways in which the combination and integration of different media forms can be exploited to stimulate experiential, intuitive, perceptual, and social/communicative aspects of learning. The goal of the project has been to develop a conceptual design model for the development of multimedia learning environments (MLEs), for humanistic learning applications, by using interactive drama. The models and methods developed though a practical design project have been founded upon theory from the realms of psychology, social sciences, learning and education, the arts and media, and software design. They address the cognitive and social aspects of learning, the use and interpretation of interactive media, the creation of learning environments, and the activities involved in design. As a vehicle to test the theoretical perspective, a design project has been undertaken, that has involved: 0 learning needs analysis and subject matter development; 9 development of a structural model for the MLE; 9 information structure, navigation and interface design; scripting, design and development of media materials for the development of interactive drama; formative evaluation. The subject area chosen for the design project is that of pregnancy and childbirth. The primary reasons for this choice was a desire to address the issues of design for informal learning experiences (that do not fit in the remit of institutional curricula) and an interest in finding ways to represent the social and interpersonal dimension to learning. Such learning processes have been described as `humanistic learning' for the purposes of this research project. To help fulfil these goals, it was decided to work with playwright Simon Turley to develop a number of interactive drama scenes. Not only did this enable some of the more sensitive and personal issues of pregnancy to be addressed, but it also gave an opportunity to explore the world of drama, film and theatre as a means to create interactive learning experiences. The research has shown the benefits of interdisciplinary design practice, produced a framework of the theoretical issues that inform designers, and developed an approach to the design of MLEs for humanistic learning applications. These elements have been brought together to form the conceptual design model.The Higher Education Funding Council For Englan

Bowdoin Orient v.130, no.1-22 (1998-1999)

https://digitalcommons.bowdoin.edu/bowdoinorient-1990s/1011/thumbnail.jp