{"type":"ScholarlyArticle","title":"Game-theoretic Analysis of Effort Allocation of Contributors to Public Projects","authors":[{"name":"Jared Soundy","slug":"jared-soundy","given":"Jared","family":"Soundy","affiliation":""},{"name":"Chenhao Wang","slug":"chenhao-wang","given":"Chenhao","family":"Wang","affiliation":""},{"name":"Clay Stevens","slug":"clay-stevens","given":"Clay","family":"Stevens","affiliation":""},{"name":"Hau Chan","slug":"hau-chan","given":"Hau","family":"Chan","affiliation":""}],"abstract":"Public projects can succeed or fail for many reasons such as the feasibility of the original goal and coordination among contributors. One major reason for failure is that insufficient work leaves the project partially completed. For certain types of projects anything short of full completion is a failure (e.g., feature request on software projects in GitHub). Therefore, project success relies heavily on individuals allocating sufficient effort. When there are multiple public projects, each contributor needs to make decisions to best allocate his/her limited effort (e.g., time) to projects while considering the effort allocation decisions of other strategic contributors and his/her parameterized utilities based on values and costs for the projects. In this paper, we introduce a game-theoretic effort allocation model of contributors to public projects for modeling effort allocation of strategic contributors. We study the related Nash equilibrium (NE) computational problems and provide NP-hardness results for the existence of NE and polynomial-time algorithms for finding NE in restricted settings. Finally, we investigate the inefficiency of NE measured by the price of anarchy and price of stability.","doi":"10.24963/ijcai.2021/57","url":"https://ijcai.org/proceedings/2021/57","pdf":"https://ijcai.org/proceedings/2021/0057.pdf","markdown":"https://ijcai.org/proceedings/2021/57.md","bibtex":"https://ijcai.org/proceedings/2021/bibtex/57","volume":{"slug":"2021","title":"Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2021","url":"https://ijcai.org/proceedings/2021/","year":2021,"location":"Montreal","dates":"19-27 August 2021","editors":"Prof. Zhi-Hua Zhou","isbn":"978-0-9992411-9-6","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2021"},"section":"Agent-based and Multi-agent Systems","track":"Main Track","number":57,"pages":{"first":405,"last":411},"keywords":["Agent-based and Multi-agent Systems: Noncooperative Games","Agent-based and Multi-agent Systems: Resource Allocation","Agent-based and Multi-agent Systems: Algorithmic Game Theory"],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}