{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,7]],"date-time":"2024-08-07T07:42:12Z","timestamp":1723016532996},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,7]]},"abstract":"<jats:p>Over the past decades in the field of machine teaching, several restrictions have been  introduced to avoid \u2018cheating\u2019, such as collusion-free or non-clashing teaching. However, these restrictions forbid several teaching situations  that  we  intuitively consider natural and fair, especially those \u2018changes of mind\u2019 of the learner as more evidence is given, affecting the likelihood of concepts and ultimately their  posteriors. Under a new generalised probabilistic teaching, not only do these non-cheating constraints look too narrow but we also show that the most relevant machine teaching models are particular cases of this framework: the consistency graph between concepts and elements simply becomes a joint probability distribution. We show a simple procedure that builds the witness joint distribution from the ground joint distribution. We prove a chain of relations, also with a theoretical lower bound, on the teaching dimension of the old and new models. Overall, this new setting is more general than the traditional machine teaching models, yet at the same time more intuitively capturing a less abrupt notion of non-cheating teaching.<\/jats:p>","DOI":"10.24963\/ijcai.2022\/412","type":"proceedings-article","created":{"date-parts":[[2022,7,15]],"date-time":"2022-07-15T22:55:56Z","timestamp":1657925756000},"page":"2973-2979","source":"Crossref","is-referenced-by-count":0,"title":["Non-Cheating Teaching Revisited: A New Probabilistic Machine Teaching Model"],"prefix":"10.24963","author":[{"given":"C\u00e8sar","family":"Ferri","sequence":"first","affiliation":[{"name":"Universitat Polit\u00e8cnica Val\u00e8ncia"}]},{"given":"Jos\u00e9","family":"Hern\u00e1ndez-Orallo","sequence":"additional","affiliation":[{"name":"Universitat Polit\u00e8cnica de Val\u00e8ncia"}]},{"given":"Jan Arne","family":"Telle","sequence":"additional","affiliation":[{"name":"University of Bergen (Norway)"}]}],"member":"10584","event":{"number":"31","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"acronym":"IJCAI-2022","name":"Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}","start":{"date-parts":[[2022,7,23]]},"theme":"Artificial Intelligence","location":"Vienna, Austria","end":{"date-parts":[[2022,7,29]]}},"container-title":["Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2022,7,18]],"date-time":"2022-07-18T07:09:34Z","timestamp":1658128174000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2022\/412"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2022,7]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2022\/412","relation":{},"subject":[],"published":{"date-parts":[[2022,7]]}}}