trolled opponents in video games is called game AI. Adaptive game AI can improve the entertainment value of games by allowing computer-controlled opponents to fix weaknesses automatically in the game AI and to respond to changes in human-player tactics. Dynamic scripting is a reinforcement learning approach to adaptive game AI that learns, during gameplay, which game tactics an opponent should ...

Current approaches to adaptive game AI require either a high quality of utilised domain knowledge, or a large number of adaptation trials. These requirements hamper the goal of rapidly adapting game AI to changing circumstances. In an alternative, novel approach, domain knowledge is gathered automatically by the game AI, and is immediately (i.e., without trials and without resource-intensive le...

Game AI is defined as the decision-making process of computercontrolled opponents in computer games. Adaptive game AI can improve the entertainment provided by computer games, by allowing the computer-controlled opponents to fix automatically weaknesses in the game AI, and to respond to changes in humanplayer tactics online, i.e., during gameplay. Successful adaptive game AI is based invariably...

Game artificial intelligence (AI) controls the decision-making process of computercontrolled opponents in computer games. Adaptive game AI (i.e., game AI that can automatically adapt the behaviour of the computer players to changes in the environment) can increase the entertainment value of computer games. Successful adaptive game AI is invariably based on the game’s domain knowledge. We show t...

We describe an approach to player-centred game design through adaptive game technologies [9]. The work presented is the result of on-going collaborative research between Media and Computing groups at the University of Ulster, and so we begin with a review of related literature from both areas before presenting our new ideas. In particular we focus on three areas of related research: understandi...

In previous work we introduced a novel approach to adaptive game AI that was focussed on the rapid and reliable adaptation to game circumstances. We named the approach ‘case-based adaptive game AI’. In the approach, domain knowledge required to adapt to game circumstances is gathered automatically by the game AI, and is exploited immediately (i.e., without trials and without resource-intensive ...

This paper shows how game analytics can be used to dynamically adapt a casual, 2-D adventure game named Sidequest: The Game (SQ:TG) in order to increase session-level retention. Our technique involves using game analytics to create an abstracted game analytic space to make the problem tractable. We then model player retention in this space and move through this space in accordance to a target d...

Adaptive learning techniques are used in numerous algorithms for classification, prediction and strategic game play1, including boosting. However, these techniques are not unique to computational learning theory. Adaptive learning approaches are also used in the social sciences2, particularly in stochastic game theory. The goal of this paper is to show that there exist significant connections b...