Thomas P. Hartley

Online action adaptation in interactive computer games

Nonplayer characters (NPCs) in todays computer games lack the ability to adapt to situations that were not envisaged by the artificial intelligence (AI) programmer. This lack of adaptation produces lifeless characters that are prone to repetitive and predictable behavior. In this article, we present our work towards the development of an online learning and adaptation architecture for NPCs in first-person shooter (FPS) computer games. Our architecture builds upon incremental case-based approaches to modelling an observed entity, and makes a number of novel contributions. In particular, we develop a dual state representation to enhance case matching, and use adaptive k-d tree-based techniques to improve case storage and retrieval. The dual state representation allows more game features to be represented in the system, which enables observed behavior to be more accurately recorded and actions predicted. The system is applied to the Unreal Tournament using the GameBots API and evaluated in a number of different game scenarios. Our results show that the adaptation system can accurately predict a human players actions and that our dual state representation enhances prediction. We also demonstrate that an adaptive k-d tree-based technique can be used online to maintain a balanced tree of observed cases.

In-game tactic adaptation for interactive computer games

Computer controlled characters in games typically lack the ability to adapt to situations that were not envisaged by the game artificial intelligence (AI) programmer. Consequently game characters tend to be lifeless and susceptible to repetitive and predictable behaviour. The focus of this work is to provide practical approaches to in-game learning and thus produce NPCs that are more believable and responsive to the human player. In this paper, we present an approach to online tactic learning and adaptation for autonomous agents in virtual environments. The design of the tactic adaptation architecture was influenced by commercial and theoretical approaches to the organisation and control of NPC behaviour in FPS games. The system is applied to Unreal Tournament using the GameBots API and evaluated in FPS game scenarios. The results show that the architecture is capable of successfully adapting NPC tactic selection and illustrate how a multi instance approach to organising tactic libraries can enhance adaptation.

Monitoring of patient fluid intake using the Xbox Kinect

This paper presents an approach that monitors patient fluid intake in real time. The approach utilizes the Microsoft Kinect, a low cost 3D sensor and the Microsoft Kinect Software Development Kit to monitor patient fluid intake. An implementation of the Naive Bayes Classifier is used to learn patient movement and classify new examples. The results from our initial experimentation show that the technique offers a promising approach to the monitoring of patient fluid intake.

Smart Terrain in Online Tactic Agent decision making process

Non-Player Characters (NPCs) are a vital part of computer games. Their behaviour is usually pre determined by the developers before a computer game is released. While these NPCs exist in a virtual environment in which they aim to achieve their objectives, these objectives might involve certain actions which should be both believable and add realism to games. In internet gameplay, these may range from navigation of the environment, attack and defense of an objective or assisting other NPCs or human players to achieve their goals. Various forms of decision making process are now implemented to provide believability and realism to games. These techniques range from reinforcement learning, imitation learning, supervised and unsupervised learning for online and offline games. While these are widely implemented, a new genre of realism is being added to games especially first person shooter games, namely Smart Terrains with virtual destructive environments. Smart Terrain has the potential to improve the realism of games and the behavior of the NPC in games such as first person shooter games where gameplay is fast paced. The potential issue would be if NPCs are dynamic enough to recognize changes in the virtual environment or if the virtual environment provides the required information to assist the NPCs with their objectives or tasks. This paper presents an overview of Smart Terrain in enhancing Online Tactic Agent decision making.

Navigational techniques to improve usability and user experience in RPG games

This paper presents the design and implementation of a mini map navigation system into an RPG Action Adventure game created using Unity3D game engine with the goal of improving the usability and user experience. The main aim of this work is to find out how a mini map navigation system can be beneficial to the end user and improve the over game play of a video game. The mini map can help reducing the user frustration, as well as aiding story progression so that it keeps the user immersed and engaged for a longer period of time that ultimately increasing the longevity of the game. A mini map navigation system is a user aid that is used across a wide range of video games and genres. The purpose of the map is to highlight the user position in relation to areas of interest such as objectives, enemies and Missions. A prototype game was created in the RPG Action Adventure genre with a vast open explorable world. The results show that the mini map has improved the overall usability and user experience.

In-game adaptation of a navigation mesh cell path

A fundamental requirement of non-player characters (NPCs) in todays computer games is to be able to move through a complex virtual world in an intelligent way. Pathfinding or path planning techniques are used by games developers to determine suitable routes, during gameplay, from a starting location to a goal position. These techniques make use of graphs to efficiently represent the game world. Navigation graphs can be created using different constructs, such as waypoints, navigation meshes and grids. Typically, path planning systems use the navigation graph to find the shortest path between locations and do not adapt in-game based on a players experience of navigating a path. In previous works we have explored approaches to in-game action prediction and tactic adaptation through machine learning inspired approaches. In this paper we present an approach to the in-game adaptation of NPC movement using navigation mesh cells. The technique allows NPCs to adapt their routes through cells based on previous experience whilst also preserving smooth paths. The system is applied to FPS game scenarios using the Unity3D game engine. The results show that the technique offers a promising approach to the adaptation of NPC movement through navigation meshes.

C# interpreter and unity 3D for educational programming games

In this paper we present an approach to creating educational programming computer games. We combine the CSI interpreter with Unity 3D to enable a player to enter program statements that can alter the game world while it is being played. We also create wrapper methods that encapsulate complex Unity C# tasks into easy to use helper functions. The results from our initial experimentation show that the technique offers a promising approach to educational programming games.

TTracker: Using finger detection to improve touch typing training

Touch typing software teaches a user to use the correct finger combinations with the correct keyboard buttons. The ultimate goal is to teach the typist to type faster, more accurately and ergonomically correct. Our research presents the working prototype of a software and hardware setup that tracks not only the speed and accuracy of the correct buttons being pressed but also which fingers are used to press them; a dimension of training that has previously not been integrated into touch typing tutorials. We use novel technology (leap motion) to detect the accurate interaction between the user and the keyboard, giving precise feedback to the user in order for him or her to improve.

Interactive reading using low cost brain computer interfaces

This work shows the feasibility for document reader user applications using a consumer grade non-invasive BCI headset. Although Brain Computer Interface (BCI) type devices are beginning to aim at the consumer level, the level at which they can actually detect brain activity is limited. There is however progress achieved in allowing for interaction between a human and a computer when this interaction is limited to around 2 actions. We employed the Emotiv Epoc, a low-priced BCI headset, to design and build a proof-of-concept document reader system that allows users to navigate the document using this low cast BCI device. Our prototype has been implemented and evaluated with 12 participants who were trained to navigate documents using signals acquired by Emotive Epoc.

Investigating control of virtual reality snowboarding simulator using a Wii FiT board

This work presents a virtual reality snowboarding application which uses a Nintendo Wii balance board for richer interaction modalities. We present the application and test the prototype with 7 participants to investigate immersion, enjoyability and to an extent performance. The outcomes from the study will be used to start forming research directions and questions to indicate likely research and development directions for future research.