Connectionist and dynamical systems approaches explain human thought, language and
behavior in terms of the emergent consequences of a large number of simple noncognitive …

Energy-efficient simultaneous localization and mapping (SLAM) is crucial for mobile robots
exploring unknown environments. The mammalian brain solves SLAM via a network of …

The embodiment stance emphasizes that cognitive processes unfold continuously in time,
are constantly linked to the sensory and motor surfaces, and adapt through learning and …

We examine the contributions of dynamic systems theory to the field of cognitive
development, focusing on modeling using dynamic neural fields. After introducing central …

Neuromorphic electronic systems exhibit advantageous characteristics, in terms of low
energy consumption and low response latency, which can be useful in robotic applications …

Infants, children, and adults have been shown to track co-occurrence across ambiguous
naming situations to infer the referents of new words. The extensive literature on this cross …

Vector Symbolic Architectures (VSA) were first proposed as connectionist models for
symbolic reasoning, leveraging parallel and in-memory computing in brains and …

Because cognitive competences emerge in evolution and development from the sensory-
motor domain, we seek a neural process account for higher cognition in which all …

Our ability to perceive a stable visual world in the presence of continuous movements of the
body, head, and eyes has puzzled researchers in the neuroscience field for a long time. We …

Embodied artificial cognitive systems, such as autonomous robots or intelligent observers,
connect cognitive processes to sensory and effector systems in real time. Prime candidates …