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There has been growing interest in creating intelligent agents in virtual worlds that do not follow fixed scripts predefined by the developers, but react accordingly based on actions performed by human players during their interaction. In order to achieve this objective, previous approaches have attempted to model the environment and the user's context directly. However, a critical component for enabling...
As wireless sensor network applications grow in complexity, ad-hoc techniques are no longer adequate. Thus, it is crucial that these systems be adaptive and autonomous to remain functional in the face of unreliable communications, dead nodes, and other unexpected failures. We propose to manage sensor networks based on a rigorous multiagent organizational design, which separates application logic from...
Group modeling is still an open challenge problem in pedestrian crowd simulations. Most existing work is based on socio-psychological models which can only describe the dynamics of pedestrians' socio-psychological states. The ability of dynamic grouping also requires that pedestrians are intelligent to behave adaptively in the ever changing environment. However, little work has incorporated the effect...
Navigation of a student over learning objects can be solved by using concept space of a domain which contains information about structural and dependency relations between concepts. Every learning object has defined relations to several concepts. Relations which exist in the learning object space also exist in the concept space between the corresponding concepts. We present an evaluation of controlled...
In the area of financial decision making it is more and more acknowledged that psychological states and characteristics play an important role, for example feeling insecure in relation to financial risks, and being greedy in relation to opportunities to obtain serious gains. This paper presents an agent model of human decision making behaviour in economic situations, incorporating a human's greed...
In this paper it is explored whether personalisation of an existing computational model of attention can increase the model's validity. Computational models of attention are for instance applied in attention allocation support systems and can benefit from this increased validity. Personalisation is done by tuning the model's parameters during a training phase, using Simulated Annealing (SA). The adapted...
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