Abstract- Despite the complexity of modern computer games and the wide range of different themes explored, there has been only a few games that feature large chaotic groups of people, such as those found at riots or protests. The most popular, State of Emergency, features hundreds of individual people on the screen at any one time, however the Artificial Intelligence (AI) that controls the rioting NPCs is fairly simplistic – the civilians run in seemingly random directions, unaffected by one another and don't seem to have specific objectives. In real protest and riot situations, each individual person involved has many factors that dictate their behaviour. Mood, temperament, behaviour of surrounding people and any perceived danger are all among the important aspects of the situation. This paper gives a brief overview of an AI mechanism that has been developed specifically for controlling riots and protests in games. The model is based on previous research into Emotional Societies and presents a realistic and believable environment for games, which can operate effectively with a relatively minimal impact on resources. Beside the potential application of the model and architecture to a computer entertainment environment, the model is generic and can be used as well for “serious ” application which involves distributed emerging behaviour, scenarios based simulation, complex agent-based modeling including emotional, reactive and deliberative reasoning. In the final paper version we will show how this model can easily be extended to support different emotional models, agent architectures, reasoning techniques, and application to a swarm of robots wandering in a hazardous environment. The emerging behaviour to avoid harmful states will be tested and validated using the model proposed in the extended abstract. 1
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