Reactive goal management in a cognitive architecture

Goals play an important role in human cognition. Different aspects of human mind influence the generation of goals they pursue, and the goals guide their behaviors. In psychology, researchers made significant efforts to study goals and their origin, and cognitive architectures include various facilities to handle goals of artificial agents. One such architecture, ICARUS, supports goal-driven behaviors while maintaining reactivity, and the top-level goals play the role of guiding ICARUS agents’ behaviors. However, the architecture covers neither the origin of its top-level goals nor the management of them, and this imposes various restrictions on ICARUS, like the limited autonomy. In this paper, we extend the architecture to provide the capability to nominate top-level goals using the notion of long-term, general goals, and manage the nominated goals by prioritizing them. For prioritization of goals, we introduce a novel capability to match concepts in a continuous manner. We show some illustrative examples in an urban driving domain, and discuss related and future work in this direction before we conclude. 2011 Elsevier B.V. All rights reserved.