SPECIAL ISSUE ON:
COGNITIVE ARCHITECTURES FOR ARTIFICIAL MINDS
Journal of Cognitive Systems Research
The design and adaptation of Cognitive Architectures (CA) is a wide and active area of research in Cognitive Science, Artificial Intelligence and, more recently, in the areas of Computational Neuroscience, Cognitive Robotics, and Computational Cognitive Systems. Cognitive architectures have been historically introduced i) to capture, at the computational level, the invariant mechanisms of human cognition, including those underlying the functions of reasoning, control, learning, memory, adaptivity, perception and action, ii) to form the basis for the development of cognitive capabilities through ontogeny over extended periods of time, and iii) to reach human level intelligence, also called AGI (Artificial General Intelligence), by means of the realisation of artificial artefacts built upon them.
During the last decades many cognitive architectures have been realised, and agents based on such infrastructures, have been widely tested in several cognitive tasks involving reasoning, learning, perception, action execution, selective attention, recognition etc.
This special issue is intended to provide an overview of the research being carried out in the interdisciplinary area of cognitively inspired AI systems designed and integrated with existing or novel CA. Both papers presenting theoretical and applied research contribution in the field are welcome.
In particular the interests of this issue are focused (but not limited to) on papers addressing the following problems: i) how different cognitive functions can be successfully integrated in general cognitive artificial agents ii) how novel integrative approaches differ and improve previous perspectives adopted in cognitive architectures iii) how the integration of cognitive architectures with external cognitive systems (e.g. specialised in specific tasks such as natural language understanding; planning, multimodal perception etc.) can improve the local performance of cognitive agents while respecting the architectural requirements of general intelligence.