{"id":{"repo_id":"unr","oai_identifier":"oai:scholarwolf.unr.edu:11714/11762"},"canonical_url":"https://search.dev.ndltd.org/etd/unr/oai:scholarwolf.unr.edu:11714/11762","repository":{"repo_id":"unr","name":"University of Nevada - Reno","base_url":"https://scholarwolf.unr.edu/server/oai/request"},"display":{"title":"Decentralized Auction Solutions for Dynamic, Networked Markets","abstract":"This work is a focused contribution to decentralized auction mechanisms inmarkets driven by autonomous, dynamically interacting nodes. These markets are characterized by strategic interactions, limited information, and fluctuating competition. Traditional auction models, such as the Second Price Auction, encourage truthful bidding but often assume centralized control, which is impractical in decentralized settings. To address this gap, we propose some extension to the Progressive Second-Price (PSP) auction, a mechanism that allows nodes to iteratively adjust bids based on local information from neighboring nodes. This work develops a dynamic framework for decision-making processes in decentralized environments, utilizing a game-theoretic approach. By process, we define a subset of right-continuous, left-limited (cadlag) valuation functions used in order to model deterministic events. Our framework represents strategies as a finite set of feasible actions, formalized through buyer--seller interactions on the bipartite graph representing participation, or the set of active bids, capturing the interdependencies between players within the network. We introduce a set of mixed strategies defined by probability distributions over these feasible actions, allowing for the modeling of intelligent decision-making within dynamic, competitive and alternatively, cooperative environments. Key contributions include the development of influence sets to capture directand indirect network effects on bidding behavior, an opt-out mechanism for strategic exit based on utility gain, derivations and proofs realizing and validating our extensions of the original theorems. Finally, we design and implement simulations to support our claims, allowing for further investigation of the solution space.","abstract_html":"This work is a focused contribution to decentralized auction mechanisms inmarkets driven by autonomous, dynamically interacting nodes. These markets are characterized by strategic interactions, limited information, and fluctuating competition. Traditional auction models, such as the Second Price Auction, encourage truthful bidding but often assume centralized control, which is impractical in decentralized settings. To address this gap, we propose some extension to the Progressive Second-Price (PSP) auction, a mechanism that allows nodes to iteratively adjust bids based on local information from neighboring nodes. This work develops a dynamic framework for decision-making processes in decentralized environments, utilizing a game-theoretic approach. By process, we define a subset of right-continuous, left-limited (cadlag) valuation functions used in order to model deterministic events. Our framework represents strategies as a finite set of feasible actions, formalized through buyer--seller interactions on the bipartite graph representing participation, or the set of active bids, capturing the interdependencies between players within the network. We introduce a set of mixed strategies defined by probability distributions over these feasible actions, allowing for the modeling of intelligent decision-making within dynamic, competitive and alternatively, cooperative environments. Key contributions include the development of influence sets to capture directand indirect network effects on bidding behavior, an opt-out mechanism for strategic exit based on utility gain, derivations and proofs realizing and validating our extensions of the original theorems. Finally, we design and implement simulations to support our claims, allowing for further investigation of the solution space.","abstract_has_math":false,"creators":["Blazek, Jordana Katherine"],"institution":null,"degree_name":null,"degree_level":"Doctorate Degree","degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Harris, Frederick C"],"committee_chairs":[],"committee_members":["Herald, Christopher","Feil-Seifer, David","Shukla, Ankita","Olson, Eric"],"year":2025,"date_issued":"2025","date_published":"2025","updated_at":"2026-07-27T21:46:30Z","subjects":[],"languages":["en_US","English"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://scholarwolf.unr.edu/handle/11714/11762","outbound_label":"Repository record","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Harris, Frederick C"]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Herald, Christopher","Feil-Seifer, David","Shukla, Ankita","Olson, Eric"]},{"key":"dc:creator","label":"Author","values":["Blazek, Jordana Katherine"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2026-01-23T20:47:32Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2026-01-23T20:47:32Z"]},{"key":"dc:date.issued","label":"Date","values":["2025"]},{"key":"dc:type","label":"Dc Type","values":["Dissertation"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Doctorate Degree"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["English"]},{"key":"dc:language.iso","label":"Language (ISO)","values":["en_US"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://scholarwolf.unr.edu/handle/11714/11762"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["This work is a focused contribution to decentralized auction mechanisms inmarkets driven by autonomous, dynamically interacting nodes. These markets are characterized by strategic interactions, limited information, and fluctuating competition. Traditional auction models, such as the Second Price Auction, encourage truthful bidding but often assume centralized control, which is impractical in decentralized settings. To address this gap, we propose some extension to the Progressive Second-Price (PSP) auction, a mechanism that allows nodes to iteratively adjust bids based on local information from neighboring nodes. This work develops a dynamic framework for decision-making processes in decentralized environments, utilizing a game-theoretic approach. By process, we define a subset of right-continuous, left-limited (cadlag) valuation functions used in order to model deterministic events. Our framework represents strategies as a finite set of feasible actions, formalized through buyer--seller interactions on the bipartite graph representing participation, or the set of active bids, capturing the interdependencies between players within the network. We introduce a set of mixed strategies defined by probability distributions over these feasible actions, allowing for the modeling of intelligent decision-making within dynamic, competitive and alternatively, cooperative environments. Key contributions include the development of influence sets to capture directand indirect network effects on bidding behavior, an opt-out mechanism for strategic exit based on utility gain, derivations and proofs realizing and validating our extensions of the original theorems. Finally, we design and implement simulations to support our claims, allowing for further investigation of the solution space."]},{"key":"dc:format","label":"Dc Format","values":["PDF"]},{"key":"dc:title","label":"Title","values":["Decentralized Auction Solutions for Dynamic, Networked Markets"]}]}],"canonical_facts":{"dc:contributor.advisor":["Harris, Frederick C"],"dc:contributor.committeemember":["Herald, Christopher","Feil-Seifer, David","Shukla, Ankita","Olson, Eric"],"dc:creator":["Blazek, Jordana Katherine"],"dc:date.accessioned":["2026-01-23T20:47:32Z"],"dc:date.available":["2026-01-23T20:47:32Z"],"dc:date.issued":["2025"],"dc:description.abstract":["This work is a focused contribution to decentralized auction mechanisms inmarkets driven by autonomous, dynamically interacting nodes. These markets are characterized by strategic interactions, limited information, and fluctuating competition. Traditional auction models, such as the Second Price Auction, encourage truthful bidding but often assume centralized control, which is impractical in decentralized settings. To address this gap, we propose some extension to the Progressive Second-Price (PSP) auction, a mechanism that allows nodes to iteratively adjust bids based on local information from neighboring nodes. This work develops a dynamic framework for decision-making processes in decentralized environments, utilizing a game-theoretic approach. By process, we define a subset of right-continuous, left-limited (cadlag) valuation functions used in order to model deterministic events. Our framework represents strategies as a finite set of feasible actions, formalized through buyer--seller interactions on the bipartite graph representing participation, or the set of active bids, capturing the interdependencies between players within the network. We introduce a set of mixed strategies defined by probability distributions over these feasible actions, allowing for the modeling of intelligent decision-making within dynamic, competitive and alternatively, cooperative environments. Key contributions include the development of influence sets to capture directand indirect network effects on bidding behavior, an opt-out mechanism for strategic exit based on utility gain, derivations and proofs realizing and validating our extensions of the original theorems. Finally, we design and implement simulations to support our claims, allowing for further investigation of the solution space."],"dc:format":["PDF"],"dc:identifier.uri":["https://scholarwolf.unr.edu/handle/11714/11762"],"dc:language":["English"],"dc:language.iso":["en_US"],"dc:title":["Decentralized Auction Solutions for Dynamic, Networked Markets"],"dc:type":["Dissertation"],"thesis:degree_level":["Doctorate Degree"]},"updated_at":"2026-07-27T21:46:30Z"}