Evolution of Biological Eye in Computer Simulation

Neil Vaughan

doi:10.1109/CEC.2019.8790284

Evolution of Biological Eye in Computer Simulation

Neil Vaughan

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

This research demonstrates an evolutionary process of a biological eye in a computer model. This demonstrates using a model, how the biological eye could have evolved, starting from a sheet of light sensitive cells towards a concave pinhole camera eye without a lens. The advantages of each iterative improvement lead to increased chance of being selected for subsequent generations because improved eye clarity helps animals to detect prey or predators. The fitness of the evolving eyes are evaluated on a range of 5 varied datasets with a range of classification algorithm tasks. The developed simulated eye model demonstrates that the requirement to detect the direction of an approaching predator does produce a gradual evolutionary transition from a flat light sensitive surface to the pinhole camera eye which models how eyes evolved in biological creatures.

Original language	English
Title of host publication	2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings
Publisher	IEEE
ISBN (Print)	9781728121529
DOIs	https://doi.org/10.1109/CEC.2019.8790284
Publication status	Published - 8 Aug 2019
Event	2019 IEEE Congress on Evolutionary Computation (CEC) - Wellington, New Zealand Duration: 10 Jun 2019 → 13 Jun 2019

Conference

Conference	2019 IEEE Congress on Evolutionary Computation (CEC)
Country/Territory	New Zealand
City	Wellington
Period	10/06/19 → 13/06/19

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10.1109/CEC.2019.8790284

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title = "Evolution of Biological Eye in Computer Simulation",

abstract = "This research demonstrates an evolutionary process of a biological eye in a computer model. This demonstrates using a model, how the biological eye could have evolved, starting from a sheet of light sensitive cells towards a concave pinhole camera eye without a lens. The advantages of each iterative improvement lead to increased chance of being selected for subsequent generations because improved eye clarity helps animals to detect prey or predators. The fitness of the evolving eyes are evaluated on a range of 5 varied datasets with a range of classification algorithm tasks. The developed simulated eye model demonstrates that the requirement to detect the direction of an approaching predator does produce a gradual evolutionary transition from a flat light sensitive surface to the pinhole camera eye which models how eyes evolved in biological creatures.",

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AB - This research demonstrates an evolutionary process of a biological eye in a computer model. This demonstrates using a model, how the biological eye could have evolved, starting from a sheet of light sensitive cells towards a concave pinhole camera eye without a lens. The advantages of each iterative improvement lead to increased chance of being selected for subsequent generations because improved eye clarity helps animals to detect prey or predators. The fitness of the evolving eyes are evaluated on a range of 5 varied datasets with a range of classification algorithm tasks. The developed simulated eye model demonstrates that the requirement to detect the direction of an approaching predator does produce a gradual evolutionary transition from a flat light sensitive surface to the pinhole camera eye which models how eyes evolved in biological creatures.

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ER -

Evolution of Biological Eye in Computer Simulation

Abstract

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