Cognitive Architectures and General Intelligent Systems
The original goal of artificial intelligence was the design and construction of computational artifacts that combined many cognitive abilities in an integrated system. These entities were intended to have the same intellectual capacity as humans and they were supposed to exhibit their intelligence in a general way across many different domains. We will refer to this research agenda as aimed at the creation of general intelligent systems. Unfortunately, modern artificial intelligence has largely abandoned this objective, having instead divided into many distinct subfields that care little about generality, intelligence, or even systems. Subfields like computational linguistics, planning, and computer vision focus their attention on specific components that underlie intelligent behavior, but seldom show concern about how they might interact with each other. Subfields like knowledge representation and machine learning focus on idealized tasks like inheritance, classification, and reactive control that ignore the richness and complexity of human intelligence. The fragmentation of artificial intelligence has taken energy away from efforts on general intelligent systems, but it has led to certain types of progress within each of its subfields. Despite this subdivision into distinct communities, the past decade has seen many applications of AI technology