{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/107917"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/107917","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Decentralized multi-user multi-armed bandits with user dependent reward distributions","abstract":"The uncoordinated spectrum access problem is studied using a multi-player multi-armed bandits framework. We consider a decentralized multi-player stochastic multi-armed bandit model where the players cannot communicate with each other and can observe only their own actions and rewards. Furthermore, the environment may appear differently to different players, i.e., the reward distributions for a given arm may vary across players. Knowledge of time horizon T is not assumed. Under these conditions, we consider two settings - zero and non-zero reward on collision (when more than one player plays the same arm). Under the zero reward on collision setting, we present a policy that achieves expected regret of O(log T) over a time horizon of duration T. While settings with non-zero rewards on collisions and varying reward distributions of arms across players have been considered separately in prior work, a model allowing for both has not been studied previously to the best of our knowledge. With this setup, we present a policy that achieves expected regret of order O(log^{2 + \\delta} T) for some 0 < \\delta < 1 over a time horizon of duration T.","abstract_html":"The uncoordinated spectrum access problem is studied using a multi-player multi-armed bandits framework. We consider a decentralized multi-player stochastic multi-armed bandit model where the players cannot communicate with each other and can observe only their own actions and rewards. Furthermore, the environment may appear differently to different players, i.e., the reward distributions for a given arm may vary across players. Knowledge of time horizon T is not assumed. Under these conditions, we consider two settings - zero and non-zero reward on collision (when more than one player plays the same arm). Under the zero reward on collision setting, we present a policy that achieves expected regret of O(log T) over a time horizon of duration T. While settings with non-zero rewards on collisions and varying reward distributions of arms across players have been considered separately in prior work, a model allowing for both has not been studied previously to the best of our knowledge. With this setup, we present a policy that achieves expected regret of order O(log^{2 + \\delta} T) for some 0 &lt; \\delta &lt; 1 over a time horizon of duration T.","abstract_has_math":false,"creators":["Magesh, Akshayaa"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Electrical & Computer Engr","degree_department":null,"school":null,"contributors":["Veeravalli, Venugopal V."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2020,"date_issued":"2020-08-26T21:54:28Z","date_published":"2020-08-26T21:54:28Z","updated_at":"2026-07-22T22:24:47Z","subjects":["multiarmed bandits, multi-player, spectrum access, decentralized"],"languages":["en"],"rights":["Copyright 2020 Akshayaa Magesh"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/107917","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Veeravalli, Venugopal V."]},{"key":"dc:creator","label":"Author","values":["Magesh, Akshayaa"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2020-08-26T21:54:28Z","2020-04-28","2020-05"]},{"key":"dc:type","label":"Dc Type","values":["text","Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical & Computer Engr"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["multiarmed bandits, multi-player, spectrum access, decentralized"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2020 Akshayaa Magesh"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/107917"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["The uncoordinated spectrum access problem is studied using a multi-player multi-armed bandits framework. We consider a decentralized multi-player stochastic multi-armed bandit model where the players cannot communicate with each other and can observe only their own actions and rewards. Furthermore, the environment may appear differently to different players, i.e., the reward distributions for a given arm may vary across players. Knowledge of time horizon T is not assumed. Under these conditions, we consider two settings - zero and non-zero reward on collision (when more than one player plays the same arm). Under the zero reward on collision setting, we present a policy that achieves expected regret of O(log T) over a time horizon of duration T. While settings with non-zero rewards on collisions and varying reward distributions of arms across players have been considered separately in prior work, a model allowing for both has not been studied previously to the best of our knowledge. With this setup, we present a policy that achieves expected regret of order O(log^{2 + \\delta} T) for some 0 < \\delta < 1 over a time horizon of duration T.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2020-08-25 without embargo terms","The student, Akshayaa Magesh, accepted the attached license on 2020-04-27 at 17:17.","The student, Akshayaa Magesh, submitted this Thesis for approval on 2020-04-27 at 17:37.","This Thesis was approved for publication on 2020-04-28 at 10:28.","DSpace SAF Submission Ingestion Package generated from Vireo submission #15063 on 2020-08-25 at 17:08:18","Made available in DSpace on 2020-08-26T21:54:28Z (GMT). No. of bitstreams: 3 MAGESH-THESIS-2020.pdf: 351083 bytes, checksum: 4db5b429c50c084b3a290778d56c7454 (MD5) MS Thesis.zip: 457094 bytes, checksum: 2624173e1733781da6a0f66597fbb263 (MD5) LICENSE.txt: 4212 bytes, checksum: 703029e2f96bec58032ef6274e4468b4 (MD5) Previous issue date: 2020-04-28"]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Decentralized multi-user multi-armed bandits with user dependent reward distributions"]}]}],"canonical_facts":{"dc:contributor":["Veeravalli, Venugopal V."],"dc:creator":["Magesh, Akshayaa"],"dc:date":["2020-08-26T21:54:28Z","2020-04-28","2020-05"],"dc:description":["The uncoordinated spectrum access problem is studied using a multi-player multi-armed bandits framework. We consider a decentralized multi-player stochastic multi-armed bandit model where the players cannot communicate with each other and can observe only their own actions and rewards. Furthermore, the environment may appear differently to different players, i.e., the reward distributions for a given arm may vary across players. Knowledge of time horizon T is not assumed. Under these conditions, we consider two settings - zero and non-zero reward on collision (when more than one player plays the same arm). Under the zero reward on collision setting, we present a policy that achieves expected regret of O(log T) over a time horizon of duration T. While settings with non-zero rewards on collisions and varying reward distributions of arms across players have been considered separately in prior work, a model allowing for both has not been studied previously to the best of our knowledge. With this setup, we present a policy that achieves expected regret of order O(log^{2 + \\delta} T) for some 0 < \\delta < 1 over a time horizon of duration T.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2020-08-25 without embargo terms","The student, Akshayaa Magesh, accepted the attached license on 2020-04-27 at 17:17.","The student, Akshayaa Magesh, submitted this Thesis for approval on 2020-04-27 at 17:37.","This Thesis was approved for publication on 2020-04-28 at 10:28.","DSpace SAF Submission Ingestion Package generated from Vireo submission #15063 on 2020-08-25 at 17:08:18","Made available in DSpace on 2020-08-26T21:54:28Z (GMT). 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