Cognitive robots: perceptual associative memory and learning
Stan Franklin · 2006
In this position paper we attempt to derive an architecture and mechanism for perceptual associative memory and learning for software agents and cognitive robots from what is known, or believed, about the same faculties in human and other animal cognition. Based on that of the IDA model of global workspace theory, a conceptual and computational model of cognition, this architecture, together with its mechanisms, offers the real possibility of autonomous software agents and cognitive robots learning their own ontologies during a developmental period. Thus the onerous chore of designing and implementing such an ontology can be avoided.