{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:22:20Z","timestamp":1760145740533,"version":"build-2065373602"},"reference-count":31,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2024,8,22]],"date-time":"2024-08-22T00:00:00Z","timestamp":1724284800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>During automated negotiations, intelligent software agents act based on the preferences of their proprietors, interdicting direct preference exposure. The agent can be armed with a component of an opponent\u2019s modeling features to reduce the uncertainty in the negotiation, but how negotiating agents with a single-peaked preference direct our attention has not been considered. Here, we first investigate the proper representation of single-peaked preferences and implementation of single-peaked agents within bidder agents using different instances of general single-peaked functions. We evaluate the modeling of single-peaked preferences and bidders in automated negotiating agents. Through experiments, we reveal that most of the opponent models can model our benchmark single-peaked agents with similar efficiencies. However, the accuracies differ among the models and in different rival batches. The perceptron-based P1 model obtained the highest accuracy, and the frequency-based model Randomdance outperformed the other competitors in most other performance measures.<\/jats:p>","DOI":"10.3390\/info15080508","type":"journal-article","created":{"date-parts":[[2024,8,23]],"date-time":"2024-08-23T12:53:19Z","timestamp":1724417599000},"page":"508","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Automated Negotiation Agents for Modeling Single-Peaked Bidders: An Experimental Comparison"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6116-1703","authenticated-orcid":false,"given":"Fatemeh","family":"Hassanvand","sequence":"first","affiliation":[{"name":"Faculty of Computer Engineering, University of Isfahan, Azadi Square, Isfahan 81746-73441, Iran"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5147-9136","authenticated-orcid":false,"given":"Faria","family":"Nassiri-Mofakham","sequence":"additional","affiliation":[{"name":"Faculty of Computer Engineering, University of Isfahan, Azadi Square, Isfahan 81746-73441, Iran"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7867-4281","authenticated-orcid":false,"given":"Katsuhide","family":"Fujita","sequence":"additional","affiliation":[{"name":"Institute of Global Innovation Research, Tokyo University of Agriculture and Technology, Tokyo 184-8588, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,8,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"279","DOI":"10.1146\/annurev.psych.51.1.279","article-title":"Negotiation","volume":"51","author":"Bazerman","year":"2000","journal-title":"Annu. 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