{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,3,29]],"date-time":"2022-03-29T00:14:14Z","timestamp":1648512854238},"reference-count":25,"publisher":"World Scientific Pub Co Pte Lt","issue":"06","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Patt. Recogn. Artif. Intell."],"published-print":{"date-parts":[[2006,9]]},"abstract":"<jats:p> Much of the allocation of human resources to tasks is studied under the rubric of \"attention\". However this is a very low-dimensional characterization of a system that has many degrees of freedom. To make progess in understanding human brain resource allocations, we will need to understand its basic functions at an abstract level. One way of accomplishing such an integration is to create a model of a human that has a useful amount of complexity. Essentially, one is faced with proposing an embodied \"operating system\" model that can be tested against human performance. Recently, technological advances have been made that allow progress in this direction. Graphic models that simulate extensive human capabilities can be used as platforms to develop synthetic models of visuo-motor behavior. Currently, such models can capture only a small portion of a full behavioral repertoire, but for the behaviors that they do model, they can describe complete visuo-motor subsystems at a level of detail that can be tested against human performance in realistic environments. This paper outlines one such model and shows both that it can produce interesting new hypotheses as to the role of vision and also that it can greatly enhance our understanding of a more multifacted characterization attention in visuo-motor tasks. <\/jats:p>","DOI":"10.1142\/s0218001406004971","type":"journal-article","created":{"date-parts":[[2006,9,25]],"date-time":"2006-09-25T10:59:17Z","timestamp":1159181957000},"page":"797-815","source":"Crossref","is-referenced-by-count":0,"title":["MODELING THE BRAIN'S OPERATING SYSTEM USING VIRTUAL HUMANOIDS"],"prefix":"10.1142","volume":"20","author":[{"given":"DANA","family":"BALLARD","sequence":"first","affiliation":[{"name":"Department of Computer Science, University of Rochester, Rochester, NY 14627, USA"}]},{"given":"NATHAN","family":"SPRAGUE","sequence":"additional","affiliation":[{"name":"Department of Mathematics and Computer Science, Kalamazoo College, Kalamazoo, MI 49006, USA"}]}],"member":"219","published-online":{"date-parts":[[2012,4,30]]},"reference":[{"key":"rf1","volume-title":"The Architecture of Cognition","author":"Anderson J.","year":"1996"},{"key":"rf2","doi-asserted-by":"crossref","first-page":"723","DOI":"10.1017\/S0140525X97001611","volume":"20","author":"Ballard D.","journal-title":"Behav. 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