Investigating the emergence of phenotypic plasticity in evolving digital organisms

Abstract
In the natural world, individual organisms can adapt as their environment changes. In most in silico evolution, however, individual organisms tend to consist of rigid solutions, with all adaptation occurring at the population level. If we are to use artificial evolving systems as a tool in understanding biology or in engineering robust and intelligent systems, however, they should be able to generate solutions with fitness-enhancing phenotypic plasticity. Here we use Avida, an established digital evolution system, to investigate the selective pressures that produce phenotypic plasticity. We witness two different types of fitness-enhancing plasticity evolve: static- execution-flow plasticity, in which the same sequence of actions produces different results depending on the environment, and dynamic-execution-flow plasticity, where organisms choose their actions based on their environment. We demonstrate that the type of plasticity that evolves depends on the environmental challenge the population faces. Finally, we compare our results to similar ones found in vastly different systems, which suggest that this phenomenon is a general feature of evolution
Keywords No keywords specified (fix it)
Categories (categorize this paper)
Options
Edit this record
Mark as duplicate
Export citation
Find it on Scholar
Request removal from index
Revision history

Download options

Our Archive


Upload a copy of this paper     Check publisher's policy     Papers currently archived: 36,003
External links

Setup an account with your affiliations in order to access resources via your University's proxy server
Configure custom proxy (use this if your affiliation does not provide a proxy)
Through your library

References found in this work BETA

No references found.

Add more references

Citations of this work BETA

No citations found.

Add more citations

Similar books and articles

Analytics

Added to PP index
2009-01-28

Total downloads
132 ( #46,683 of 2,293,925 )

Recent downloads (6 months)
1 ( #412,139 of 2,293,925 )

How can I increase my downloads?

Monthly downloads

My notes

Sign in to use this feature