[{"title":"Learning Boolean Specifications","doi":"10.1016/j.artint.2015.09.003","date_updated":"2022-01-06T06:59:10Z","publisher":"Elsevier","date_created":"2018-06-25T10:43:19Z","author":[{"full_name":"Bubeck, Uwe","last_name":"Bubeck","first_name":"Uwe"},{"first_name":"Hans","full_name":"Kleine Büning, Hans","last_name":"Kleine Büning"}],"year":"2015","page":"246 - 257","citation":{"ama":"Bubeck U, Kleine Büning H. Learning Boolean Specifications. <i>Artificial Intelligence</i>. 2015:246-257. doi:<a href=\"https://doi.org/10.1016/j.artint.2015.09.003\">10.1016/j.artint.2015.09.003</a>","ieee":"U. Bubeck and H. Kleine Büning, “Learning Boolean Specifications,” <i>Artificial Intelligence</i>, pp. 246–257, 2015.","chicago":"Bubeck, Uwe, and Hans Kleine Büning. “Learning Boolean Specifications.” <i>Artificial Intelligence</i>, 2015, 246–57. <a href=\"https://doi.org/10.1016/j.artint.2015.09.003\">https://doi.org/10.1016/j.artint.2015.09.003</a>.","apa":"Bubeck, U., &#38; Kleine Büning, H. (2015). Learning Boolean Specifications. <i>Artificial Intelligence</i>, 246–257. <a href=\"https://doi.org/10.1016/j.artint.2015.09.003\">https://doi.org/10.1016/j.artint.2015.09.003</a>","bibtex":"@article{Bubeck_Kleine Büning_2015, title={Learning Boolean Specifications}, DOI={<a href=\"https://doi.org/10.1016/j.artint.2015.09.003\">10.1016/j.artint.2015.09.003</a>}, journal={Artificial Intelligence}, publisher={Elsevier}, author={Bubeck, Uwe and Kleine Büning, Hans}, year={2015}, pages={246–257} }","mla":"Bubeck, Uwe, and Hans Kleine Büning. “Learning Boolean Specifications.” <i>Artificial Intelligence</i>, Elsevier, 2015, pp. 246–57, doi:<a href=\"https://doi.org/10.1016/j.artint.2015.09.003\">10.1016/j.artint.2015.09.003</a>.","short":"U. Bubeck, H. Kleine Büning, Artificial Intelligence (2015) 246–257."},"publication_identifier":{"issn":["0004-3702"]},"keyword":["Query learning","Propositional logic"],"ddc":["000"],"language":[{"iso":"eng"}],"_id":"3343","project":[{"_id":"1","name":"SFB 901"},{"name":"SFB 901 - Project Area B","_id":"3"},{"name":"SFB 901 - Subproject B2","_id":"10"}],"department":[{"_id":"34"}],"user_id":"315","abstract":[{"text":"In this paper we consider an extended variant of query learning where the hidden concept is embedded in some Boolean circuit. This additional processing layer modifies query arguments and answers by fixed transformation functions which are known to the learner. For this scenario, we provide a characterization of the solution space and an ordering on it. We give a compact representation of the minimal and maximal solutions as quantified Boolean formulas and we adapt the original algorithms for exact learning of specific classes of propositional formulas.","lang":"eng"}],"status":"public","publication":"Artificial Intelligence","type":"journal_article"}]