Modelling Human Vision for Heuristics
Authors
Sean McGerty, Frank Moisladis
Corresponding Author
Sean McGerty
Available Online December 2013.
- DOI
- https://doi.org/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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Sean McGerty AU - Frank Moisladis PY - 2013/12 DA - 2013/12 TI - Modelling Human Vision for Heuristics BT - 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 - https://doi.org/10.2991/visio-13.2014.7 ID - McGerty2013/12 ER -