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We observe and acknowledge, as many other researchers do, that action plays a key role in providing content to the sensory state. We propose a simple, yet powerful learning criterion, that of invariance, where invariance simply means that the internal state does not change over time. We show that after reinforcement learning based on the invariance criterion, the property of action sequence based on an internal sensory state accurately reflects the property of the stimulus that triggered that internal state. That way, the meaning of the internal sensory state can be firmly grounded on the property of that particular action sequence. We expect the framing of the problem and the proposed solution presented in this paper to help shed new light on autonomous understanding in developmental agents such as humanoid robots.<\/jats:p>","DOI":"10.1142\/s0219843607001102","type":"journal-article","created":{"date-parts":[[2007,7,5]],"date-time":"2007-07-05T09:38:16Z","timestamp":1183628296000},"page":"211-243","source":"Crossref","is-referenced-by-count":16,"title":["AUTONOMOUS LEARNING OF THE SEMANTICS OF INTERNAL SENSORY STATES BASED ON MOTOR EXPLORATION"],"prefix":"10.1142","volume":"04","author":[{"given":"YOONSUCK","family":"CHOE","sequence":"first","affiliation":[{"name":"Department of Computer Science, Texas A&amp;M University, College Station, TX 77843, USA"}]},{"given":"HUEI-FANG","family":"YANG","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Texas A&amp;M University, College Station, TX 77843, USA"}]},{"given":"DANIEL CHERN-YEOW","family":"ENG","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Texas A&amp;M University, College Station, TX 77843, USA"}]}],"member":"219","published-online":{"date-parts":[[2011,11,20]]},"reference":[{"key":"rf1","doi-asserted-by":"publisher","DOI":"10.1126\/science.291.5504.599"},{"key":"rf2","doi-asserted-by":"publisher","DOI":"10.1080\/09540090310001655110"},{"key":"rf3","doi-asserted-by":"publisher","DOI":"10.1142\/S0219843604000149"},{"key":"rf4","doi-asserted-by":"publisher","DOI":"10.1016\/S1364-6613(99)01440-0"},{"key":"rf5","doi-asserted-by":"publisher","DOI":"10.1016\/0004-3702(91)90053-M"},{"key":"rf6","doi-asserted-by":"crossref","DOI":"10.7551\/mitpress\/6979.001.0001","volume-title":"Understanding Intelligence","author":"Pfeifer R.","year":"1999"},{"key":"rf7","unstructured":"O.\u00a0Sporns, The Handbook of Brain Theory and Neural Networks, 2nd edn., ed. 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