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Recent studies demonstrate that AI agents trained with deep reinforcement learning are capable of collaborating with humans. These studies primarily evaluate human compatibility through \u201cobjective\u201d metrics such as task performance, obscuring potential variation in the levels of trust and subjective preference that different agents garner. To better understand the factors shaping subjective preferences in human-agent cooperation, we train deep reinforcement learning agents in Coins, a two-player social dilemma. We recruit <jats:inline-formula><jats:alternatives><jats:tex-math>$$N = 501$$<\/jats:tex-math><mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\">\n                  <mml:mrow>\n                    <mml:mi>N<\/mml:mi>\n                    <mml:mo>=<\/mml:mo>\n                    <mml:mn>501<\/mml:mn>\n                  <\/mml:mrow>\n                <\/mml:math><\/jats:alternatives><\/jats:inline-formula> participants for a human-agent cooperation study and measure their impressions of the agents they encounter. Participants\u2019 perceptions of warmth and competence predict their stated preferences for different agents, above and beyond objective performance metrics. Drawing inspiration from social science and biology research, we subsequently implement a new \u201cpartner choice\u201d framework to elicit <jats:italic>revealed<\/jats:italic> preferences: after playing an episode with an agent, participants are asked whether they would like to play the next episode with the same agent or to play alone. As with stated preferences, social perception better predicts participants\u2019 revealed preferences than does objective performance. Given these results, we recommend human-agent interaction researchers routinely incorporate the measurement of social perception and subjective preferences into their studies.<\/jats:p>","DOI":"10.1007\/s10458-024-09649-6","type":"journal-article","created":{"date-parts":[[2024,5,22]],"date-time":"2024-05-22T05:01:40Z","timestamp":1716354100000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":31,"title":["Warmth and competence in human-agent cooperation"],"prefix":"10.1007","volume":"38","author":[{"given":"Kevin R.","family":"McKee","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xuechunzi","family":"Bai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Susan\u00a0T.","family":"Fiske","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,5,22]]},"reference":[{"issue":"2","key":"9649_CR1","doi-asserted-by":"crossref","first-page":"290","DOI":"10.1037\/rev0000262","volume":"128","author":"AE Abele","year":"2021","unstructured":"Abele, A. 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