Contracting With Uncertain Level Of Trust | Semantic Scholar Skip to search formSkip to main content> Semantic Scholar's Logo Search Sign InCreate Free Account You are currently offline. Some features of the site may not work correctly. DOI:10.1111/1467-8640.00200 Corpus ID: 33473191Contracting With Uncertain Level Of Trust @article{Braynov2002ContractingWU, title={Contracting With Uncertain Level Of Trust}, author={S. Braynov and T. Sandholm}, journal={Computational Intelligence}, year={2002}, volume={18} } S. Braynov, T. Sandholm Published 2002 Business, Computer Science Computational Intelligence The paper investigates the impact of trust on market efficiency and bilateral contracts. We prove that a market in which agents are trusted to the degree they deserve to be trusted is as efficient as a market with complete trustworthiness. In other words, complete trustworthiness is not a necessary condition for market efficiency. We prove that distrust could significantly reduce market efficiency, and we show how to solve the problem by using appropriately designed multiagent contracts. The… CONTINUE READING View on Wiley wikidata.org Save to Library Create Alert Cite Launch Research Feed Share This Paper 81 CitationsHighly Influencial Citations 4 Background Citations 41 Methods Citations 4 View All Topics from this paper. Explore Further: Topics Discussed in This Paper Trust (emotion) Bilateral filter Agent-based model Trusted operating system Norm (social) Distrust Smart contract 81 Citations Citation Type Citation Type All Types Cites Results Cites Methods Cites Background Has PDF Publication Type Author More Filters More Filters Filters Sort by Relevance Sort by Most Influenced Papers Sort by Citation Count Sort by Recency Monopolizing markets by exploiting trust S. Sen, D. 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Intell. 2000 570 PDF Save Alert Research Feed ‹ 1 2 3 › Related Papers Abstract Topics 81 Citations 26 References Related Papers Stay Connected With Semantic Scholar Sign Up About Semantic Scholar Semantic Scholar is a free, AI-powered research tool for scientific literature, based at the Allen Institute for AI. Learn More → Resources DatasetsSupp.aiAPIOpen Corpus Organization About UsResearchPublishing PartnersData Partners   FAQContact Proudly built by AI2 with the help of our Collaborators Terms of Service•Privacy Policy The Allen Institute for AI By clicking accept or continuing to use the site, you agree to the terms outlined in our Privacy Policy, Terms of Service, and Dataset License ACCEPT & CONTINUE