This research addresses the challenges associated with the supervision of game development projects as part of a capstone experience. The context of this research is the capstone experience as undertaken by third year software development students who have chosen to develop a game for their project at the School of Information and Communication Technology (ICT) at the Nelson Mandela Metropolitan University (NMMU). This research begins by determining the curricular requirements with respect to the capstone experience for Information Technology (IT) qualifications. This is done by investigating the applicable documentation at the international, national and departmental levels. The position of game development as a sub-category of software development is established and the Indie paradigm is investigated as a further sub-category of game development. Furthermore, the Indie paradigm is investigated through in-depth analyses of the techniques used in the development of ten Indie games. This investigation serves to identify the commonly used techniques in the Indie paradigm. The research presents a case study of the game development projects at the School of ICT at the NMMU for the period from 2009 to 2013. This case study combined with the techniques identifed from the Indie paradigm forms the basis of the guidelines presented by this research. The guidelines are subject to a review by an industry expert. The review takes the form of an expert interview, which serves to verify the guidelines. This research concludes by demonstrating alignment with the objectives it set out to achieve and motivating the success of the research conducted.

A research report submitted to the Faculty of Humanities, University of the Witwatersrand, Johannesburg, in partial fulfilment of the requirements for the degree of Master Arts in Digital Animation, March 2017 / XL2018

by Horace Wai-Kit, Chan. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1996. / Includes bibliographical references (leaves 109-112). / Acknowledgement --- p.i / Abstract --- p.ii / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Overview --- p.1 / Chapter 1.2 --- Objective --- p.3 / Chapter 1.3 --- Organization of This Thesis --- p.3 / Chapter 2 --- Background --- p.5 / Chapter 2.1 --- Definitions --- p.5 / Chapter 2.1.1 --- Theoretical Definition of Solving a Game --- p.5 / Chapter 2.1.2 --- Definition of Computer Go --- p.7 / Chapter 2.2 --- State of the Art of Computer Go --- p.7 / Chapter 2.3 --- A Framework for Computer Go --- p.11 / Chapter 2.3.1 --- Evaluation Function --- p.11 / Chapter 2.3.2 --- Plausible Move Generator --- p.14 / Chapter 2.4 --- Problems Tackled in this Research --- p.14 / Chapter 3 --- Application of TD in Game Playing --- p.15 / Chapter 3.1 --- Introduction --- p.15 / Chapter 3.2 --- Reinforcement Learning and TD Learning --- p.15 / Chapter 3.2.1 --- Models of Learning --- p.16 / Chapter 3.2.2 --- Temporal Difference Learning --- p.16 / Chapter 3.3 --- TD Learning and Game-playing --- p.20 / Chapter 3.3.1 --- Game-Playing as a Delay-reward Prediction Problem --- p.20 / Chapter 3.3.2 --- Previous Work of TD Learning in Backgammon --- p.20 / Chapter 3.3.3 --- Previous Works of TD Learning in Go --- p.22 / Chapter 3.4 --- Design of this Research --- p.23 / Chapter 3.4.1 --- Limitations in the Previous Researches --- p.24 / Chapter 3.4.2 --- Motivation --- p.25 / Chapter 3.4.3 --- Objective and Methodology --- p.26 / Chapter 4 --- Deriving a New Updating Rule to Apply TD Learning in Multi-layer Perceptron --- p.28 / Chapter 4.1 --- Multi-layer Perceptron (MLP) --- p.28 / Chapter 4.2 --- Derivation of TD(A) Learning Rule for MLP --- p.31 / Chapter 4.2.1 --- Notations --- p.31 / Chapter 4.2.2 --- A New Generalized Delta Rule --- p.31 / Chapter 4.2.3 --- Updating rule for TD(A) Learning --- p.34 / Chapter 4.3 --- Algorithm of Training MLP using TD(A) --- p.35 / Chapter 4.3.1 --- Definitions of Variables in the Algorithm --- p.35 / Chapter 4.3.2 --- Training Algorithm --- p.36 / Chapter 4.3.3 --- Description of the Algorithm --- p.39 / Chapter 5 --- Experiments --- p.41 / Chapter 5.1 --- Introduction --- p.41 / Chapter 5.2 --- Experiment 1 : Training Evaluation Function for 7 x 7 Go Games by TD(λ) with Self-playing --- p.42 / Chapter 5.2.1 --- Introduction --- p.42 / Chapter 5.2.2 --- 7 x 7 Go --- p.42 / Chapter 5.2.3 --- Experimental Designs --- p.43 / Chapter 5.2.4 --- Performance Testing for Trained Networks --- p.44 / Chapter 5.2.5 --- Results --- p.44 / Chapter 5.2.6 --- Discussions --- p.45 / Chapter 5.2.7 --- Limitations --- p.47 / Chapter 5.3 --- Experiment 2 : Training Evaluation Function for 9 x 9 Go Games by TD(λ) Learning from Human Games --- p.47 / Chapter 5.3.1 --- Introduction --- p.47 / Chapter 5.3.2 --- 9x 9 Go game --- p.48 / Chapter 5.3.3 --- Training Data Preparation --- p.49 / Chapter 5.3.4 --- Experimental Designs --- p.50 / Chapter 5.3.5 --- Results --- p.52 / Chapter 5.3.6 --- Discussion --- p.54 / Chapter 5.3.7 --- Limitations --- p.56 / Chapter 5.4 --- Experiment 3 : Life Status Determination in the Go Endgame --- p.57 / Chapter 5.4.1 --- Introduction --- p.57 / Chapter 5.4.2 --- Training Data Preparation --- p.58 / Chapter 5.4.3 --- Experimental Designs --- p.60 / Chapter 5.4.4 --- Results --- p.64 / Chapter 5.4.5 --- Discussion --- p.65 / Chapter 5.4.6 --- Limitations --- p.66 / Chapter 5.5 --- A Postulated Model --- p.66 / Chapter 6 --- Conclusions --- p.69 / Chapter 6.1 --- Future Direction of Research --- p.71 / Chapter A --- An Introduction to Go --- p.72 / Chapter A.l --- A Brief Introduction --- p.72 / Chapter A.1.1 --- What is Go? --- p.72 / Chapter A.1.2 --- History of Go --- p.72 / Chapter A.1.3 --- Equipment used in a Go game --- p.73 / Chapter A.2 --- Basic Rules in Go --- p.74 / Chapter A.2.1 --- A Go game --- p.74 / Chapter A.2.2 --- Liberty and Capture --- p.75 / Chapter A.2.3 --- Ko --- p.77 / Chapter A.2.4 --- "Eyes, Live and Death" --- p.81 / Chapter A.2.5 --- Seki --- p.83 / Chapter A.2.6 --- Endgame and Scoring --- p.83 / Chapter A.2.7 --- Rank and Handicap Games --- p.85 / Chapter A.3 --- Strategies and Tactics in Go --- p.87 / Chapter A.3.1 --- Strategy vs Tactics --- p.87 / Chapter A.3.2 --- Open-game --- p.88 / Chapter A.3.3 --- Middle-game --- p.91 / Chapter A.3.4 --- End-game --- p.92 / Chapter B --- Mathematical Model of Connectivity --- p.94 / Chapter B.1 --- Introduction --- p.94 / Chapter B.2 --- Basic Definitions --- p.94 / Chapter B.3 --- Adjacency and Connectivity --- p.96 / Chapter B.4 --- String and Link --- p.98 / Chapter B.4.1 --- String --- p.98 / Chapter B.4.2 --- Link --- p.98 / Chapter B.5 --- Liberty and Atari --- p.99 / Chapter B.5.1 --- Liberty --- p.99 / Chapter B.5.2 --- Atari --- p.101 / Chapter B.6 --- Ko --- p.101 / Chapter B.7 --- Prohibited Move --- p.104 / Chapter B.8 --- Path and Distance --- p.105 / Bibliography --- p.109

The purpose of this project on game design and development is to experiment with actual technology tools used in computer games and get experience in three deminsional game development using 3D Studio Max and Microsoft XNA.

No description available.

Video game players demand a volume of content far in excess of the ability of game designers to create it. For example, a single quest might take a week to develop and test, which means that companies such as Blizzard are spending millions of dollars each month on new content for their games. As a result, both players and developers are frustrated with the inability to meet the demand for new content. By generating content on-demand, it is possible to create custom content for each player based on player preferences. It is also possible to make use of the current world state during generation, something which cannot be done with current techniques. Using developers to create rules and assets for a content generator instead of creating content directly will lower development costs as well as reduce the development time for new game content to seconds rather than days. This work is part of the field of computational creativity, and involves the use of computers to create aesthetically pleasing game content, such as terrain, characters, and quests. I demonstrate agent-based terrain generation, and economic modeling of game spaces. I also demonstrate the autonomous generation of quests for online role playing games, and the ability to play these quests using an emulated Everquest server.

The recent transformation of consumer graphics (CG) cards into powerful 3D rendering processors is due in large measure to the success of game developers in delivering mass market entertainment software that feature highly immersive and captivating virtual environments. Despite this success, 3D CG application development is becoming increasingly handicapped by the inability of traditional content creation methods to keep up with the demand for content. The term content is used here to refer to any data operated on by application code that is meant for viewing, including 3D models, textures, animation sequences and maps or other data-intensive descriptions of virtual environments. Traditionally, content has been handcrafted by humans. A serious problem facing the interactive graphics software development community is how to increase the rate at which content can be produced to keep up with the increasingly rapid pace at which software for interactive applications can now be developed. Research addressing this problem centers around procedural content creation systems. By moving away from purely human content creation toward systems in which humans play a substantially less time-intensive but no less creative part in the process, procedural content creation opens new doors. From a qualitative standpoint, these types of systems will not rely less on human intervention but rather more since they will depend heavily on direction from a human in order to synthesize the desired content. This research draws heavily from the entertainment software domain but the research is broadly relevant to 3D graphics applications in general.

The project focuses on computer tools suitable for particular game genres and how they are used to develop 3D computer games. As part of learning about the tools, the author developed a 3D computer adventure game called "Adventures of Smiley" using Macromedia Director MX and 3D Studio Max. The game's purpose is to engage children using a friendly interface while they learn about different topics in various subject areas through lessons and puzzles. The research gathered information about the current game industry, technologies and game genres, which can be used as a reference for the beginning level game programmer. The project documentation and the game are also published on the Internet and can be freely accessed online.

This project included the development of a multi-user game that takes place in a 3 dimensional world of the computer science department. Basically, the game allows prospective students to meet existing students and faculty in a virtual open house that takes place within the third floor of Jack Brown Hall. Users can walk around Jack Brown Hall and type text messages to chat with each other.

Computer games are an increasingly popular application for Artificial Intelligence (AI) research, and conversely AI is an increasingly popular selling point for commercial digital games. AI for non playing characters (NPC) in computer games tends to come from people with computing skills well beyond the average user. The prime reason behind the lack of involvement of novice users in creating AI behaviors for NPC's in computer games is that construction of high quality AI behaviors is a hard problem. There are two reasons for it. First, creating a set of AI behavior requires specialized skills in design and programming. The nature of the process restricts it to certain individuals who have a certain expertise in this area. There is little understanding of how the behavior authoring process can be simplified with easy-to-use authoring environments so that novice users (without programming and design experience) can carry out the behavior authoring task. Second, the constructed AI behaviors have problems and bugs in them which cause a break in player expe- rience when the problematic behaviors repeatedly fail. It is harder for novice users to identify, modify and correct problems with the authored behavior sets as they do not have the necessary debugging and design experience. The two issues give rise to a couple of interesting questions that need to be investigated: a) How can the AI behavior construction process be simplified so that a novice user (without program- ming and design experience) can easily conduct the authoring activity and b) How can the novice users be supported to help them identify and correct problems with the authored behavior sets? In this thesis, I explore the issues related to the problems highlighted and propose a solution to them within an application domain, named Second Mind(SM). In SM novice users who do not have expertise in computer programming employ an authoring interface to design behaviors for intelligent virtual characters performing a service in a virtual world. These services range from shopkeepers to museum hosts. The constructed behaviors are further repaired using an AI based approach. To evaluate the construction and repair approach, we conduct experiments with human subjects. Based on developing and evaluating the solution, I claim that a design solution with behavior timeline based interaction design approach for behavior construction supported by an understandable vocabulary and reduced feature representation for- malism enables novice users to author AI behaviors in an easy and understandable manner for NPCs performing a service in a virtual world. I further claim that an introspective reasoning approach based on comparison of successful and unsuccessful execution traces can be used as a means to successfully identify breaks in player ex- perience and modify the failures to improve the experience of the player interacting with NPCs performing a service in a virtual world. The work contributes in the following three ways by providing: 1) a novel introspective reasoning approach for successfully detecting and repairing failures in AI behaviors for NPCs performing a service in a virtual world.; 2) a novice user understandable authoring environment to help them create AI behaviors for NPCs performing a service in a virtual world in an easy and understandable manner; and 3) Design, debugging and testing scaffolding to help novice users modify their authored AI behaviors and achieve higher quality modified AI behaviors compared to their original unmodified behaviors.