Unified theories of cognition
Adaptive search through constraint violations
Journal of Experimental & Theoretical Artificial Intelligence
A reinforcement learning-based architecture for fuzzy logic control
International Journal of Approximate Reasoning - Special issue on fuzzy logic and neural networks for pattern recognition and control
Chunking in Soar: The Anatomy of a General Learning Mechanism
Machine Learning
Motivated Behavior for Goal Adoption
Selected Papers from the 4th Australian Workshop on Distributed Artificial Intelligence, Multi-Agent Systems: Theories, Languages, and Applications
An Architecture for Persistent Reactive Behavior
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 2
Machine Learning
Relational temporal difference learning
ICML '06 Proceedings of the 23rd international conference on Machine learning
A unified cognitive architecture for physical agents
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
Teleo-reactive programs for agent control
Journal of Artificial Intelligence Research
Journal of Artificial Intelligence Research
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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.