Towards a Self-Organized Agent-Based Simulation Model for Exploration of Human Synaptic Connections
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.
- Publication:
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arXiv e-prints
- Pub Date:
- July 2012
- DOI:
- 10.48550/arXiv.1207.3760
- arXiv:
- arXiv:1207.3760
- Bibcode:
- 2012arXiv1207.3760G
- Keywords:
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- Computer Science - Neural and Evolutionary Computing;
- Computer Science - Artificial Intelligence;
- Computer Science - Machine Learning;
- Nonlinear Sciences - Adaptation and Self-Organizing Systems
- E-Print:
- 4 pages, 1 figure, 2nd Computer Science Student Workshop