Symbolic and Hybrid Models of Cognition

For decades, symbolic models of cognition were the dominant computational approaches of cognition. Today they coexist with subsymbolic, statistical, and hybrid models, but they are still the de facto standard for modeling human reasoning processes. This chapter summarizes important aspects of symbolic and hybrid models of cognition, approaching the topic from different perspectives. After some discussion on historical aspects and the theoretical basis of symbolic models of cognition, cognitive architectures as models for intelligent agents are examined. Subsequently, the role of symbolic computational approaches towards processing natural language, representation of human knowledge, and commonsense reasoning are considered. Then the focus is put on the crucial question of learning new representations and theories, before finally looking at hybrid and neural-symbolic systems combining reasoning and learning and bridging between symbolic and subsymbolic elements.