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This paper presents an artificial cognitive system tightly integrating object perception and manipulation for assistive robotics.
We then provide a series of recommendations to facilitate the development of the perceptual, motor, and cognitive architecture for this proposed artificial cognitive system in future work.
The major goal of the COSPAL project is to develop an artificial cognitive system architecture, with the ability to autonomously extend its capabilities.
In particular, can we assess whether the 'fluid' or 'crystallised' intelligence of an artificial cognitive system is changing during its cognitive development as a result of acquiring more concepts?
The co-driver is an artificial cognitive system, which implements the mirroring mechanism posited in above cited theories on human empathy [1, 2, 3, 4, 5, 6].
Within the EU interactIVe project [7] the Authors adopted the same conceptual framework for developing an artificial cognitive system (named co-driver) able to understand the driver intentions and to produce a variety of Driver Assistance Functions [8, 9, 10].
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Learning and generating serially ordered sequences of actions is a core component of cognition both in organisms and in artificial cognitive systems.
Despite advances in both cognitive brain research and in the development of brain-inspired artificial cognitive systems, the interplay of these key ingredients of cognition remain largely elusive and unquantified in complex real-world tasks.
This book offers a concise and accessible introduction to the emerging field of artificial cognitive systems.
OACs are designed to capture the interaction between objects and associated actions in artificial cognitive systems.
Drawing on artificial intelligence, developmental psychology, and cognitive neuroscience, the field of artificial cognitive systems has as its ultimate goal the creation of computer-based systems that can interact with humans and serve society in a variety of ways.
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