Modelling Human Vision for Heuristics

DOI

10.2991/visio-13.2014.7How to use a DOI?

Keywords

vision, attention, artificial intelligence, evolution, satisficing, particle swarm, genetic algorithm, simulated annealing, mutation.

Abstract

Human vision is a highly complex system that has evolved to enable interactions within and on our environment in an expedient and resource efficient way. Applying black box testing principles gives us insight to functional parameterizations within the brain. Neuroscience further helps us understand the localization of functions within the brain. By modeling these specializations we gain a taxonomy for interactions between focused and persistent attention modes. Using this taxonomy we break down the interactions within evolutionary heuristic showing possibilities for granular hybrid behaviors. Finally we correlate this approach in a byplay between strategic and tactical concerns in military simulation.

Copyright

© 2014, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Sean McGerty
AU  - Frank Moisladis
PY  - 2013/12
DA  - 2013/12
TI  - Modelling Human Vision for Heuristics
BT  - Proceedings of the 2013 International Conference on Computer Graphics,Visualization, Computer Vision, and Game Technology
PB  - Atlantis Press
SP  - 38
EP  - 45
SN  - 1951-6851
UR  - https://doi.org/10.2991/visio-13.2014.7
DO  - 10.2991/visio-13.2014.7
ID  - McGerty2013/12
ER  -