A Closed-Loop Toolchain for Neural Network Simulations of Learning Autonomous Agents.

ABSTRACT: Neural network simulation is an important tool for generating and evaluating hypotheses on the structure, dynamics, and function of neural circuits. For scientific questions addressing organisms operating autonomously in their environments, in particular where learning is involved, it is crucial to be able to operate such simulations in a closed-loop fashion. In such a set-up, the neural agent continuously receives sensory stimuli from the environment and provides motor signals that manipulate the environment or move the agent within it. So far, most studies requiring such functionality have been conducted with custom simulation scripts and manually implemented tasks. This makes it difficult for other researchers to reproduce and build upon previous work and nearly impossible to compare th

SUBMITTER: Jordan J 

PROVIDER: S-EPMC6687756 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature