Abstract
OPINION article Front. Neurorobot., 15 November 2017 Volume 11 - 2017 | https://doi.org/10.3389/fnbot.2017.00063
Highlights
Understanding cognitive functions and mechanisms of development in animals is essential for the future generation of more intelligent systems (Hirel et al, 2011; Hassabis et al, 2017)
Recent progresses in cognitive sciences and developmental neurobiology have promoted a new branch of robotics named “Cognitive Developmental Robotics (CDR)” (Asada et al, 2009; Asada, 2013; Min et al, 2016)
CDR has emerged as a scientific field of research aiming to develop robots with abilities to effectively interact with dynamic environments and show brain-like cognitive abilities such as memory and learning
Summary
The field of modern robotics is seeking approaches to develop artificial systems to execute tasks in less predefined dynamic environments Such robotic systems should learn from information extracted from the environment to demonstrate actions like natural intelligence (Mataric, 1998). Recent progresses in cognitive sciences and developmental neurobiology have promoted a new branch of robotics named “Cognitive Developmental Robotics (CDR)” (Asada et al, 2009; Asada, 2013; Min et al, 2016) Such robots behave in response to a dynamic environment by Spiking Neural Networks based controllers. To construct a software of a CDR system, a computational model of agent-environment interaction that define dynamical response of the CDR executed by a SNN with a sufficient architecture is required It is done as follows (Asada et al, 2009; Asada, 2013; Xu et al, 2014): Step 1. If hypothesis does not work, propose a new hypothesis and go to step 1
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