{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,4,4]],"date-time":"2022-04-04T12:38:29Z","timestamp":1649075909809},"reference-count":7,"publisher":"World Scientific Pub Co Pte Lt","issue":"04","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Comp. Intel. Appl."],"published-print":{"date-parts":[[2001,12]]},"abstract":"<jats:p> We show how event extraction can be used for handling delayed response tasks with arbitrary delay periods between the stimulus and the cue for response. We use a simple recurrent network for solving the task. Our approach is based on a number of information processing levels, where the lowest level works on raw time-step based sensory data. This data is classified using an unsupervised clustering mechanism. The second level works on this classified data, but still on the individual time-step basis. An event extraction mechanism detects and signals transitions between classes; this forms the basis for the third level. As this level only is updated when events occur, it is independent of the time-scale of the lower level interaction. We also sketch how an event filtering mechanism could be constructed which discards irrelevant data from the event stream. Such a mechanism would output a fourth level representation which could be used for delayed response tasks where irrelevant, or distracting, events could occur during the delay. <\/jats:p>","DOI":"10.1142\/s1469026801000330","type":"journal-article","created":{"date-parts":[[2002,7,27]],"date-time":"2002-07-27T10:58:59Z","timestamp":1027767539000},"page":"413-426","source":"Crossref","is-referenced-by-count":3,"title":["LEARNING DELAYED RESPONSE TASKS THROUGH UNSUPERVISED EVENT EXTRACTION"],"prefix":"10.1142","volume":"01","author":[{"given":"FREDRIK","family":"LIN\u00c5KER","sequence":"first","affiliation":[{"name":"Department of Computer Science, University of Sk\u00f6vde, Post Office Box 408, SE-541 28 Sk\u00f6vde, Sweden"},{"name":"Department of Computer Science, University of Sheffield, Regent Court, 211 Portobello Street, Sheffield S1 4DP, United Kingdom"}]},{"given":"HENRIK","family":"JACOBSSON","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Sk\u00f6vde, Post Office Box 408, SE-541 28 Sk\u00f6vde, Sweden"},{"name":"Department of Computer Science, University of Sheffield, Regent Court, 211 Portobello Street, Sheffield S1 4DP, United Kingdom"}]}],"member":"219","published-online":{"date-parts":[[2012,1,25]]},"reference":[{"key":"p_2","doi-asserted-by":"publisher","DOI":"10.1023\/A:1009645229062"},{"key":"p_3","doi-asserted-by":"publisher","DOI":"10.1109\/72.279181"},{"key":"p_4","doi-asserted-by":"publisher","DOI":"10.1080\/095400999116313"},{"key":"p_8","doi-asserted-by":"publisher","DOI":"10.1109\/JRA.1986.1087032"},{"key":"p_9","first-page":"727","author":"Grossberg S.","year":"1987","journal-title":"Proceedings of the IEEE international conference on neural networks"},{"key":"p_12","doi-asserted-by":"publisher","DOI":"10.1207\/s15516709cog1402_1"},{"key":"p_15","doi-asserted-by":"publisher","DOI":"10.1016\/0010-0277(93)90058-4"}],"container-title":["International Journal of Computational Intelligence and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S1469026801000330","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,7]],"date-time":"2019-08-07T13:50:30Z","timestamp":1565185830000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/abs\/10.1142\/S1469026801000330"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2001,12]]},"references-count":7,"journal-issue":{"issue":"04","published-online":{"date-parts":[[2012,1,25]]},"published-print":{"date-parts":[[2001,12]]}},"alternative-id":["10.1142\/S1469026801000330"],"URL":"https:\/\/doi.org\/10.1142\/s1469026801000330","relation":{},"ISSN":["1469-0268","1757-5885"],"issn-type":[{"value":"1469-0268","type":"print"},{"value":"1757-5885","type":"electronic"}],"subject":[],"published":{"date-parts":[[2001,12]]}}}