Computational Models of Cognition

Abstract

Having looked at the development of cognitive abilities from the perspective of psychology and neuroscience, we now shift our sights to recent attempts at building artificial cognitive systems. In the following, we will focus on cognitive architectures rather than on specific cognitive systems. We do this because cognitive architectures are normally taken as the point of departure for the construction of a cognitive system and they encapsulate the various assumptions we make when designing a cognitive system. Consequently, there are many different types of cognitive architecture. To provide a framework for our survey of cognitive architectures, we must first address these assumptions and we will do this by beginning our discussion with an overview of the different paradigms of cognition. We have already discussed one approach to cognition in Chap. 1 — enaction — and we will take the opportunity here to position enaction within the overall scheme of cognition paradigms. With the differences between the different paradigms of cognition established, we can then move on to discuss the importance of cognitive architectures and survey the cognitive architecture literature, classifying each architecture according to its paradigm and highlighting the extent to which each architecture addresses the different characteristics of cognition. We will make this survey as complete as possible but we will emphasize those architectures that are intended to be used with physical robots and those that provide some developmental capability. On the basis of this review of cognitive architectures — both general characteristics and specific instances — we will conclude with a summary of the essential and desirable features that a cognitive architecture should exhibit if it is to be capable of forming the basis of a system that can autonomously develop cognitive abilities.