Towards a Self-Organized Agent-Based Simulation Model for Exploration of Human Synaptic Connections
Neural and Evolutionary Computing
2012-07-17 v1 Artificial Intelligence
Machine Learning
Adaptation and Self-Organizing Systems
Abstract
In this paper, the early design of our self-organized agent-based simulation model for exploration of synaptic connections that faithfully generates what is observed in natural situation is given. While we take inspiration from neuroscience, our intent is not to create a veridical model of processes in neurodevelopmental biology, nor to represent a real biological system. Instead, our goal is to design a simulation model that learns acting in the same way of human nervous system by using findings on human subjects using reflex methodologies in order to estimate unknown connections.
Cite
@article{arxiv.1207.3760,
title = {Towards a Self-Organized Agent-Based Simulation Model for Exploration of Human Synaptic Connections},
author = {Önder Gürcan and Carole Bernon and Kemal S. Türker},
journal= {arXiv preprint arXiv:1207.3760},
year = {2012}
}
Comments
4 pages, 1 figure, 2nd Computer Science Student Workshop