Increaing Sia Architecture Realism by Modeling and Adapting to Affect and Personality

  • Eva Hudlicka
Part of the Multiagent Systems, Artificial Societies, and Simulated Organizations book series (MASA, volume 3)


The ability to exhibit, recognize and respond to different affective states is a key aspect of social interaction. To enhance their believability and realism, socially intelligent agent architectures must be capable of modeling and generating behavior variations due to distinct affective states on the one hand, and to recognize and adapt to such variations in the human user / collaborator on the other. This chapter describes an adaptive user interface system capable of recognizing and adapting to the user’s affective and belief state: the Affect and Belief Adaptive Interface System (ABAIS). ABAIS architecture implements a four-phase adaptive methodology and provides a generic adaptive framework for exploring a variety of user affect assessment methods and GUI adaptation strategies. An ABAIS prototype was implemented and demonstrated in the context of an Air Force combat task, using a knowledge-based approach to assess and adapt to the pilot’s anxiety level.


Affective State Compensatory Strategy Belief State Diagnostic Task Impact Prediction 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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© Kluwer Academic Publishers 2002

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  • Eva Hudlicka

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