The　problem　of　finding　partners　is　concerned　with　how　to　identify　some　specific　entities　(agents)　from　a　group　that　will　be　able　to　provide　certain　requested　services.　This　problem　can　readily　be　found　in　applications　such　as　file　sharing　and　task　allocation　in　open　and/or　distributed　environments.　Previous　studies　have　shown　that　entities　can　effectively　select　their　partners　by　means　of　evaluating　their　mutual　trust　relationships.　Here　a　trust　relationship　between　two　entities　refers　to　the　establishment　of　one　entity＇s　belief　that　another　entity　will　be　able　to　accomplish　a　service　of　interest.　In　this　work,　we　aim　to　study　how　the　partner-finding　problem　can　be　more　effectively　and　efficiently　solved　by　allowing　entities　to　autonomously　update　their　beliefs　and　hence　trust　relationships　based　on　their　past　experiences.　In　doing　so,　we　introduce　the　notion　of　a　trust　network　in　which　nodes　correspond　to　entities　and　links　represent　trust　relationships　between　entities.　We　apply　the　methodology　of　Autonomy-Oriented　Computing　(AOC)　to　model　and　simulate　the　behavior-based　trust　relationship　updates　of　entities　over　time,　as　well　as　the　structural　characteristics　of　the　trust　network　as　being　established　by　entities.　Besides　providing　detailed　formulations,　we　perform　a　series　of　experiments　to　evaluate　the　impacts　of　the　proposed　trust　relationship　update　mechanism　on　the　performance　of　partner　finding.