Generating Compact Wasp Nest Structures via Minimal Complexity Algorithms.

<p>Many models have been developed to explain the process of self organization-the emergence of seemingly purposeful behaviors from groups of entities with limited individual intelligence. However, the underlying behavior that facilitates the emergence of this global pattern is not generally well understood. Our study focuses on different low complexity building algorithms and characterizes how nests are built using these algorithms. Three rules postulated to be functions of wasps' building behavior were developed. First is the random rule, in which there is no constraint per the choice of site to be initiated. The second is the 2-cell rule where only sites with at least two ready walls are initiated. Third, the maxWall rule ensures only sites with the maximum number of ready walls are initiated. This work provides better insight and visualization through simulation into wasps building behavior. This acquired knowledge can be applied to robotics and distributed optimization processes.</p>

Name thesis:degree_name

MS (Master of Science)

Level thesis:degree_level

Thesis - unrestricted

Discipline thesis:degree_discipline

Computer and Information Science

Year dc:date.issued

2010

Author dc:creator

• Adoe, Fadel Ewusi Kofi

• Self organization
• Stigmergy
• Wasp nest
• Computer Sciences
• Physical Sciences and Mathematics
• Theory and Algorithms

Statement dc:rights

• Copyright by the authors.

Repository record dc:identifier

https://dc.etsu.edu/etd/1683

OAI identifier oai:identifier

oai:dc.etsu.edu:etd-3038