Abstract/Details

DNAgents: Genetically engineered intelligent mobile agents


2010 2010

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Abstract (summary)

Mobile agents are a useful paradigm for network coding providing many advantages and disadvantages. Unfortunately, widespread adoption of mobile agents has been hampered by the disadvantages, which could be said to outweigh the advantages. There is a variety of ongoing work to address these issues, and this is discussed. Ultimately, genetic algorithms are selected as the most interesting potential avenue. Genetic algorithms have many potential benefits for mobile agents. The primary benefit is the potential for agents to become even more adaptive to situational changes in the environment and/or emergent security risks. There are secondary benefits such as the natural obfuscation of functions inherent to genetic algorithms. Pitfalls also exist, namely the difficulty of defining a satisfactory fitness function and the variable execution time of mobile agents arising from the fact that it exists on a network. DNAgents 1.0, an original application of genetic algorithms to mobile agents is implemented and discussed, and serves to highlight these difficulties. Modifications of traditional genetic algorithms are also discussed. Ultimately, a combination of genetic algorithms and artificial life is considered to be the most appropriate approach to mobile agents. This allows the consideration of agents to be organisms, and the network to be their environment. Towards this end, a novel framework called DNAgents 2.0 is designed and implemented. This framework allows the continual evolution of agents in a network without having a separate training and deployment phase. Parameters for this new framework were defined and explored. Lastly, an experiment similar to DNAgents 1.0 is performed for comparative purposes against DNAgents 1.0 and to prove the viability of this new framework.

Indexing (details)


Subject
Artificial intelligence;
Computer science
Classification
0800: Artificial intelligence
0984: Computer science
Identifier / keyword
Applied sciences; Artificial life; Intelligent agents; Mobile agents
Title
DNAgents: Genetically engineered intelligent mobile agents
Author
Kackley, Jeremy Otho
Number of pages
107
Publication year
2010
Degree date
2010
School code
0211
Source
DAI-B 71/10, Dissertation Abstracts International
Place of publication
Ann Arbor
Country of publication
United States
ISBN
9781124250809
Advisor
Ali, Dia
University/institution
The University of Southern Mississippi
University location
United States -- Mississippi
Degree
Ph.D.
Source type
Dissertations & Theses
Language
English
Document type
Dissertation/Thesis
Dissertation/thesis number
3424879
ProQuest document ID
756364748
Copyright
Database copyright ProQuest LLC; ProQuest does not claim copyright in the individual underlying works.
Document URL
http://search.proquest.com/docview/756364748
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