This thesis deals with game development on the Xbox 360 platform and implementation of a starter kit for this platform. After introduction of the Xbox 360 as a modern and very powerful gaming console, the XNA technology that makes development of games for console possible for the first time in history not only for professionals but also for amateurs, is introduced. The next part mentions existing starter kits for 3D XNA games, existing tools widely used to analyze implemented solution with focus on performance and tools commonly used for game content creation. The main part of thesis is dedicated to design, implementation and testing of a real time strategy starter kit prototype, with emphasis on efficiency, understandability and usability by XNA community members in mind.

<p>Artificial intelligence (AI) is already a fundamental component of computer games. In this context is emotions a growing part in simulating real life. The proposed emotional state module, provides a way for the game agents to select an action in real-time virtual environments. The modules function has been tested with the open-source strategy game ORTS. This thesis proposes a new approach for the design of an interacting network, similar to a spreading activation system, of emotional states that keeps track of emotion intensities changing and interacting over time. The network of emotions can represent any number of persisting states, such as moods, emotions and drives. Any emotional signal can affect every state positively or negatively. The states' response to emotional signals are influenced by the other states represented in the network. The network is contained within an emotional state module. This interactions between emotions are not the focus of much research, neither is the representation model. The focus tend to be on the mechanisms eliciting emotions and on how to express the emotions.</p>

Artificial intelligence (AI) is already a fundamental component of computer games. In this context is emotions a growing part in simulating real life. The proposed emotional state module, provides a way for the game agents to select an action in real-time virtual environments. The modules function has been tested with the open-source strategy game ORTS. This thesis proposes a new approach for the design of an interacting network, similar to a spreading activation system, of emotional states that keeps track of emotion intensities changing and interacting over time. The network of emotions can represent any number of persisting states, such as moods, emotions and drives. Any emotional signal can affect every state positively or negatively. The states' response to emotional signals are influenced by the other states represented in the network. The network is contained within an emotional state module. This interactions between emotions are not the focus of much research, neither is the representation model. The focus tend to be on the mechanisms eliciting emotions and on how to express the emotions.

This thesis presents optimization techniques for efficient rendering of complex scenes on mobile devices. The introductory part of the text describes Unity game engine and the topic of mobile game development using this tool. Then follows a presentation of important optimization principles and methods for terrain rendering, large scale rendering of animated objects, rendering of animated water surfaces and of other elements in the scenes. The described methods include both general principles of optimization and specific optimization approaches based on the features of Unity game engine. The implementation of presented methods is described and used in practice in the context of mobile strategy game development.

This dissertation set out to understand the decision processes used by decision makers in adversarial environment by setting up an adversarial decision making microworld, as an experimental platform, using a real time strategy (RTS) game called Rise of Nations (RON). The specific objectives of this dissertation were: 1.Contribute to the validation of recognition-primed decision (RPD) model in a simulated adversarial environment; 2.Explore the roles of common-sense strategies in decision making in the adversarial environment; and 3.Test the effectiveness of training recommendations based on the RPD model. Three related experimental studies were setup to investigate each of the objectives. Study 1 found that RPD model was partly valid where RPD processes were prevalently used but other decision processes were also important in an adversarial environment. A new decision model (ConPAD model) was proposed to capture the nature of decision making in the adversarial environment. It was also found that cognitive abilities might have some effects on the types of decision processes used by the decision makers. Study 2 found that common-sense strategies were prevalent in the adversarial environment where the participants were able to use all but one of the warfare related strategies extracted from literature without teaching them. The strategy familiarization training was not found to significantly improve decision making but showed that common-sense strategies were prevalent and simple familiarization training was not sufficient to produce differences in strategy usage and performances from the novice participants. Study 3 also found that RPD based training (cue-recognition and decision skill training) were not significant in producing better performance although subjective feedback found such training to be useful. However, the participants with RPD based training conditions were able to perform on the same level as the expert participants bridging the gap between novices and experts. Based on the findings, it was recommended that decision training should involve not just RPD based training, but comparisons of attributes as well. A more interactive training combining common-sense strategies, cue-recognition and decision skill training might be more useful. More theoretical experimentation would be required to validate the new decision model proposed in this dissertation. / Ph. D.