To build systems as resourceful and adaptive as people, we must develop cognitive architectures that support great procedural and representational diversity. No single technique is by itself powerful enough to deal with the broad range of domains every ordinary person can understand—even as children, we can effortlessly think about complex problems involving temporal, spatial, physical, bodily, psychological, and social dimensions. In this chapter, we describe a multiagent cognitive architecture that aims for such flexibility. Rather than seeking a best way to organize agents, our architecture supports multiple “ways to think,” each a different architectural configuration of agents. Each agent may use a different way to represent and reason with knowledge, and there are special “panalogy” mechanisms that link agents that represent similar ideas in different ways. At the highest level, the architecture is arranged as a matrix of agents: Vertically, the architecture divides into a tower of reflection, including the reactive, deliberative, reflective, self-reflective, and self-conscious levels; horizontally, the architecture divides along “mental realms,” including the temporal, spatial, physical, bodily, social, and psychological realms. Our goal is to build an artificial intelligence (AI) system resourceful enough to combine the advantages of many different ways to think about things, by making use of many types of mechanisms for reasoning, representation, and reflection.
Evolutionary aspects of reservoir computing