ﻻ يوجد ملخص باللغة العربية
There is much to learn through synthesis of Developmental Biology, Cognitive Science and Computational Modeling. One lesson we can learn from this perspective is that the initialization of intelligent programs cannot solely rely on manipulation of numerous parameters. Our path forward is to present a design for developmentally-inspired learning agents based on the Braitenberg Vehicle. Using these agents to exemplify artificial embodied intelligence, we move closer to modeling embodied experience and morphogenetic growth as components of cognitive developmental capacity. We consider various factors regarding biological and cognitive development which influence the generation of adult phenotypes and the contingency of available developmental pathways. These mechanisms produce emergent connectivity with shifting weights and adaptive network topography, thus illustrating the importance of developmental processes in training neural networks. This approach provides a blueprint for adaptive agent behavior that might result from a developmental approach: namely by exploiting critical periods or growth and acquisition, an explicitly embodied network architecture, and a distinction between the assembly of neural networks and active learning on these networks.
The connection between brain and behavior is a longstanding issue in the areas of behavioral science, artificial intelligence, and neurobiology. Particularly in artificial intelligence research, behavior is generated by a black box approximating the
Cell fate decisions in multicellular organisms are precisely coordinated, leading to highly reproducible macroscopic outcomes of developmental processes. The origins of this reproducibility can be found at the molecular level during the earliest stag
As the human brain develops, it increasingly supports coordinated control of neural activity. The mechanism by which white matter evolves to support this coordination is not well understood. We use a network representation of diffusion imaging data f
Developmental processes in multicellular organisms occur far from equilibrium, yet produce complex patterns with astonishing reproducibility. We measure the precision and reproducibility of bilaterally symmetric fly wings across the natural range of
The connectome, or the entire connectivity of a neural system represented by network, ranges various scales from synaptic connections between individual neurons to fibre tract connections between brain regions. Although the modularity they commonly s