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.
","abstract_html":"<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>","abstract_has_math":false,"creators":["Adoe, Fadel Ewusi Kofi"],"institution":null,"degree_name":"MS (Master of Science)","degree_level":"Thesis - unrestricted","degree_discipline":"Computer and Information Science","degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2010,"date_issued":"2010-05-08T07:00:00Z","date_published":"2010-05-08T07:00:00Z","updated_at":"2026-07-24T02:20:42Z","subjects":["Self organization","Stigmergy","Wasp nest","Computer Sciences","Physical Sciences and Mathematics","Theory and Algorithms"],"languages":[],"rights":["Copyright by the authors."],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://dc.etsu.edu/etd/1683","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Adoe, Fadel Ewusi Kofi"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.issued","label":"Date","values":["2010-05-08T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer and Information Science"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis - unrestricted"]},{"key":"thesis:degree_name","label":"Degree Name","values":["MS (Master of Science)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Self organization","Stigmergy","Wasp nest","Computer Sciences","Physical Sciences and Mathematics","Theory and Algorithms"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["Copyright by the authors."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://dc.etsu.edu/context/etd/article/3038/viewcontent/AdoeF042710f.pdf","https://dc.etsu.edu/etd/1683"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["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.
"]},{"key":"dc:title","label":"Title","values":["Generating Compact Wasp Nest Structures via Minimal Complexity Algorithms."]}]}],"canonical_facts":{"dc:creator":["Adoe, Fadel Ewusi Kofi"],"dc:date.issued":["2010-05-08T07:00:00Z"],"dc:description.abstract":["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.
"],"dc:identifier":["https://dc.etsu.edu/context/etd/article/3038/viewcontent/AdoeF042710f.pdf","https://dc.etsu.edu/etd/1683"],"dc:rights":["Copyright by the authors."],"dc:subject":["Self organization","Stigmergy","Wasp nest","Computer Sciences","Physical Sciences and Mathematics","Theory and Algorithms"],"dc:title":["Generating Compact Wasp Nest Structures via Minimal Complexity Algorithms."],"thesis:degree_discipline":["Computer and Information Science"],"thesis:degree_level":["Thesis - unrestricted"],"thesis:degree_name":["MS (Master of Science)"]},"updated_at":"2026-07-24T02:20:42Z"}