RT Journal Article
A1 Alessandro Di Nuovo
A1 Tim Jay

PB iet
T1 Development of numerical cognition in children and artificial systems: a review of the current knowledge and proposals for multi-disciplinary research
JN Cognitive Computation and Systems
VO 1
IS 1
SP 2
OP 11
AB Numerical cognition is a distinctive component of human intelligence such that the observation of its practice provides a window in high-level brain function. The modelling of numerical abilities in artificial cognitive systems can help to confirm existing child development hypotheses and define new ones by means of computational simulations. Meanwhile, new research will help to discover innovative principles for the design of artificial agents with advanced reasoning capabilities and clarify the underlying algorithms (e.g. deep learning) that can be highly effective but difficult to understand for humans. This study promotes new investigation by providing a common resource for researchers with different backgrounds, including computer science, robotics, neuroscience, psychology, and education, who are interested in pursuing scientific collaboration on mutually stimulating research on this topic. The study emphasises the fundamental role of embodiment in the initial development of numerical cognition in children. This strong relationship with the body motivates the cognitive developmental robotics (CDR) approach for new research that can (among others) help standardise data collection and provide open databases for benchmarking computational models. Furthermore, the authors discuss the potential application of robots in classrooms and argue that the CDR approach can be extended to assist educators and favour mathematical education.
K1 artificial cognitive systems
K1 children
K1 child development hypotheses
K1 advanced reasoning capabilities
K1 human intelligence
K1 artificial agents
K1 numerical cognition
K1 high-level brain function
K1 computational simulations
K1 artificial systems
K1 mathematical education
K1 cognitive developmental robotics approach
DO https://doi.org/10.1049/ccs.2018.0004
UL https://digital-library.theiet.org/;jsessionid=2kowmtdt2lf5d.x-iet-live-01content/journals/10.1049/ccs.2018.0004
LA English
SN
YR 2019
OL EN