الفهرس 
AcknowledgementOnly 14 pages are availabe for public view
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Abstract
In recent years, the computer games industry has grown to reach dozens of billions of dollars creating a need for evolving game story management techniques. This field has become the center of a lot of research through the last couple of years. This field of research aims to provide an effective way to follow and interpret the player’s response throughout the game and use this info to define the next event that should be presented to the player and make any needed in scene customization. The usual game stories are either linear which means that playing the game would be like playing a movie where the player doesn’t really have a choice to change anything or branching which means the story has one start and two possible ending for example or player-created which gives the player the maximum control over the game but which usually ends up creating a story whose events are totally random and the story is usually very minimal. This thesis aims to provide a way to combine the first and the last types to provide the player a consistent and structured story while giving the maximum sense of agency possible to increase enjoyment and replay value. This thesis suggests a new method to follow the player moves and responses to form a model of the player personality characteristics and playing style and use this model to select and present the suitable event to the player which when played would gather further info about the player further updating the player model. A Rules engine is used in the selection and analysis of the event suitability and also in the character model updates.