?url_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rft.title=Covert+Perceptual+Capability+Development&rft.creator=Huang%2C+Xiao&rft.creator=Weng%2C+Juyang&rft.subject=Statistical+Models&rft.subject=Machine+Learning&rft.subject=Robotics&rft.description=In+this+paper%2C+we+propose+a+model+to+develop%0Arobots%E2%80%99+covert+perceptual+capability+using+reinforcement+learning.+Covert+perceptual+behavior+is+treated+as+action+selected+by+a+motivational+system.+We+apply+this+model+to%0Avision-based+navigation.+The+goal+is+to+enable%0Aa+robot+to+learn+road+boundary+type.+Instead%0Aof+dealing+with+problems+in+controlled+environments+with+a+low-dimensional+state+space%2C%0Awe+test+the+model+on+images+captured+in+non-stationary+environments.+Incremental+Hierarchical+Discriminant+Regression+is+used+to%0Agenerate+states+on+the+fly.+Its+coarse-to-fine%0Atree+structure+guarantees+real-time+retrieval%0Ain+high-dimensional+state+space.+K+Nearest-Neighbor+strategy+is+adopted+to+further+reduce+training+time+complexity.&rft.publisher=Lund+University+Cognitive+Studies&rft.contributor=Berthouze%2C+Luc&rft.contributor=Kaplan%2C+Fr%C3%A9d%C3%A9ric&rft.contributor=Kozima%2C+Hideki&rft.contributor=Yano%2C+Hiroyuki&rft.contributor=Konczak%2C+J%C3%BCrgen&rft.contributor=Metta%2C+Giorgio&rft.contributor=Nadel%2C+Jacqueline&rft.contributor=Sandini%2C+Giulio&rft.contributor=Stojanov%2C+Georgi&rft.contributor=Balkenius%2C+Christian&rft.date=2005&rft.type=Conference+Paper&rft.type=PeerReviewed&rft.format=application%2Fpdf&rft.identifier=http%3A%2F%2Fcogprints.org%2F4981%2F1%2Fhuang.pdf&rft.identifier=++Huang%2C+Xiao+and+Weng%2C+Juyang++(2005)+Covert+Perceptual+Capability+Development.++%5BConference+Paper%5D+++++&rft.relation=http%3A%2F%2Fcogprints.org%2F4981%2F