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Deliverable WP3 D3.1: Critical Comparison of Attention, Monitoring and Control Architectures
This deliverable provides a critical comparison of a number of current attention, monitoring and control architectures and gives a theoretically analysis and comparison of different architectures to identify their weaknesses and strengths. Models concerned with bottom-up attention, top-down attention, reinforcement control of attention, emulation, schemas, context processing and priming are considered. It is shown that no current model is able to handle all these mechanisms but that there exist many subsystems that could potentially be combined into a more capable system. The goal of this text is to provide a critical comparison of architectures for attention, monitoring and control. This comparison is put within the overal goal of the MindRACES project which is to (1) incorporate anticipatory functionalities into existing cognitive models; (2) improve anticipatory functionalities of existing cognitive models; (3) integrate different anticipatory functionalities of cognitive models. There will thus be an emphasis on the role of prediction and anticipation in the different models that are compared. As few current models aim at including all aspects of attention, monitoring and control it is not possible to compare such architectures with each other in a straight forward manner. Instead, the path taken here is to list and compare models that address some of the mechanisms related to attention, monitoring and control. Since most attention systems to date relate to visual attention rather than attention in general, many of the systems will have vision as the target modality. The current overview will form a base for improving existing models and architectures and will provide a theoretical comparison by identifying the currently best models for attention, epistemic actions, constructive perception with context effects and priming effects. Possible improvements will also be stated for future integration into a more complete architecture.
Deliverable WP3 D3.2
 
 

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Anticipatory Cognitive Science is a research field that ensembles artificial intelligence, biology, psychology, neurology, engineering and philosophy in order to build anticipatory cognitive systems that are able to face human tasks with the same anticipatory capabilities and performance. In deep: Cognitive science is the interdisciplinary study of mind and intelligence, embracing philosophy, psychology, artificial intelligence, neuroscience, linguistics, and anthropology. Its intellectual origins are in the mid-1950s when researchers in several fields began to develop theories of mind based on complex representations and computational procedures. Its organizational origins are in the mid-1970s when the Cognitive Science Society was formed and the journal Cognitive Science began. Since then, more than sixty universities in North America, Europe, Asia, and Australia have established cognitive science programs, and many others have instituted courses in cognitive science.