A Fully Automated Negotiator for Structured Faculty-University Contract Negotiations Using Deep Reinforcement Learning

A Fully Automated Negotiator for Structured Faculty-University Contract Negotiations Using Deep Reinforcement Learning | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A Fully Automated Negotiator for Structured Faculty-University Contract Negotiations Using Deep Reinforcement Learning Milad Rezamand, Rupp Carriveau, Matt Davison, Robert Watts This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7803642/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This paper proposes a decentralized negotiator model which can be employed to conduct negotiation between University and Faculty stakeholders under well defined terms. The proposed model employs deep reinforcement learning (DRL) to support negotiation policies and achieve Pareto optimal agreements under constraints and priorities of both parties. Fine-grained analysis of the model is conducted to explore the impact of weight updating on negotiation outcomes, and a case study is conducted to measure the model performance using real-world contract situations. The iterative process of negotiation, i.e., negotiation of compensation, research funding, workload, and tenure expectations, is considered to identify the model's decision-making process.. Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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