001387561 000__ 03424cam\a2200541Ma\4500 001387561 001__ 1387561 001387561 003__ MaCbMITP 001387561 005__ 20240325105119.0 001387561 006__ m\\\\\o\\d\\\\\\\\ 001387561 007__ cr\cn\nnnunnun 001387561 008__ 970402s1998\\\\maua\\\\ob\\\\001\0\eng\d 001387561 020__ $$a0585031037$$q(electronic bk.) 001387561 020__ $$a9780585031033$$q(electronic bk.) 001387561 020__ $$a9780262041645 001387561 020__ $$a0262041642 001387561 020__ $$a9780262271875 001387561 020__ $$a0262271877 001387561 035__ $$a(OCoLC)42854442$$z(OCoLC)42417217$$z(OCoLC)60848001$$z(OCoLC)156944278$$z(OCoLC)508286753$$z(OCoLC)532418043$$z(OCoLC)551730505$$z(OCoLC)695610861$$z(OCoLC)961598091$$z(OCoLC)962716221$$z(OCoLC)970722830$$z(OCoLC)990614938$$z(OCoLC)990761827$$z(OCoLC)1007408386$$z(OCoLC)1038549098$$z(OCoLC)1044065840$$z(OCoLC)1052977982$$z(OCoLC)1055830122$$z(OCoLC)1077924084$$z(OCoLC)1097344551 001387561 035__ $$a(OCoLC-P)42854442 001387561 040__ $$aOCoLC-P$$beng$$epn$$cOCoLC-P 001387561 050_4 $$aTJ211.35$$b.D67 1998eb 001387561 072_7 $$aTEC$$x037000$$2bisacsh 001387561 08204 $$a629.8/92$$221 001387561 1001_ $$aDorigo, Marco. 001387561 24510 $$aRobot shaping :$$ban experiment in behavior engineering /$$cMarco Dorigo and Marco Colombetti. 001387561 260__ $$aCambridge, Mass. :$$bMIT Press,$$c©1998. 001387561 264_4 $$c©1998 001387561 300__ $$a1 online resource (xviii, 203 pages) :$$billustrations. 001387561 336__ $$atext$$btxt$$2rdacontent 001387561 337__ $$acomputer$$bc$$2rdamedia 001387561 338__ $$aonline resource$$bcr$$2rdacarrier 001387561 4901_ $$aIntelligent robotics and autonomous agents 001387561 500__ $$a"A Bradford book." 001387561 506__ $$aAccess limited to authorized users. 001387561 520__ $$aForeword by Lashon BookerTo program an autonomous robot to act reliably in a dynamic environment is a complex task. The dynamics of the environment are unpredictable, and the robots' sensors provide noisy input. A learning autonomous robot, one that can acquire knowledge through interaction with its environment and then adapt its behavior, greatly simplifies the designer's work. A learning robot need not be given all of the details of its environment, and its sensors and actuators need not be finely tuned. Robot Shaping is about designing and building learning autonomous robots. The term "shaping" comes from experimental psychology, where it describes the incremental training of animals. The authors propose a new engineering discipline, "behavior engineering," to provide the methodologies and tools for creating autonomous robots. Their techniques are based on classifier systems, a reinforcement learning architecture originated by John Holland, to which they have added several new ideas, such as "mutespec," classifier system "energy," and dynamic population size. In the book they present Behavior Analysis and Training (BAT) as an example of a behavior engineering methodology. 001387561 588__ $$aOCLC-licensed vendor bibliographic record. 001387561 650_0 $$aRobots$$xControl systems. 001387561 650_0 $$aMachine learning. 001387561 650_0 $$aRobots$$xMotion. 001387561 653__ $$aCOMPUTER SCIENCE/Robotics & Agents 001387561 655_0 $$aElectronic books 001387561 7001_ $$aColombetti, Marco. 001387561 852__ $$bebk 001387561 85640 $$3MIT Press$$uhttps://univsouthin.idm.oclc.org/login?url=https://doi.org/10.7551/mitpress/5988.001.0001?locatt=mode:legacy$$zOnline Access through The MIT Press Direct 001387561 85642 $$3OCLC metadata license agreement$$uhttp://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf 001387561 909CO $$ooai:library.usi.edu:1387561$$pGLOBAL_SET 001387561 980__ $$aBIB 001387561 980__ $$aEBOOK 001387561 982__ $$aEbook 001387561 983__ $$aOnline