4.5 Globalist versus Localist Representations 81 gorization of visual memory contents takes place by retrieving object and scene categories from DUAL’s semantic memory and mapping them onto current visual memory representations. RVA VWM Scene X ( “a A ae afention — <i ~~. re eT 1 ee _—- B Olb--_-T AL a a ai a B fe oy i. “DUAL coalihon a — DUAL Semantic Memory / f two-column text mm) ttle ~~ eft column kdleden a a Fig. 4.10: The three main components of the DUAL model: the retinotopic visual array (RVA), the visual working memory (VWM) and DUAL’s semantic memory. Attention is allocated to an area of the visual array by the object in VWM controlling attention, while scene and object categories corresponding to the contents of VWM are retrieved from the semantic memory. In principle the DUAL framework seems quite powerful; using the language of CogPrime, however, it seems to us that the learning mechanisms of DUAL have not been formulated in such a way as to give rise to powerful, scalable cognitive synergy. It would likely be possible to create very powerful AGI systems within DUAL, and perhaps some very CogPrime -like systems as well. But the systems that have been created or designed for use within DUAL so far seem not to be that powerful in their potential or scope. 4.5.4 4D/RCS In a rather different direction, James Albus, while at the National Bureau of Standards, de- veloped a very thorough and impressive architecture for intelligent robotics called 4D/RCS, which was implemented in a number of machines including unmanned automated vehicles. This architecture lacks critical aspects of intelligence such as learning and creativity, but combines perception, action, planning and world-modeling in a highly effective and tightly-integrated fashion. The architecture has three hierarchies of memory /processing units: one for perception, one for action and one for modeling and guidance. Each unit has a certain spatiotemporal scope, HOUSE_OVERSIGHT_012997