A hybrid cognitive-reactive multi-agent controller

• Published in: IEEE/RSJ International Conference on Intelligent Robots and Systems Vol. 3; pp. 2807 - 2812 vol.3
• Main Authors: Bugajska, M.D., Schultz, A.C., Trafton, J.G., Taylor, M., Mintz, F.E.
• Format: Conference Proceeding
• Language: English
• Published: Piscataway NJ IEEE 2002
• Subjects: Applied sciences; Artificial intelligence; Autonomous agents; Cognition; Cognitive robotics; Computational modeling; Computer architecture; Computer science; control theory; systems; Control theory. Systems; Evolutionary computation; Exact sciences and technology; Pattern recognition. Digital image processing. Computational geometry; Reconnaissance; Remotely operated vehicles; Robot sensing systems; Robotics; Surveillance; Rule based system; Evolutionary algorithm; Hybrid control; Discrete system; Hybrid system; Learning systems; Reactive system; Cognitive theory; Computational learning; Educational software program; Multiagent system; Surveillance; Genetic algorithm; Learning algorithm; Continuous system; Monitoring; Adaptation
• ISBN: 0780373987; 9780780373983
• DOI: 10.1109/IRDS.2002.1041695

The purpose of this paper is to introduce a hybrid cognitive-reactive system, which integrates a machine-learning algorithm (SAMUEL, an evolutionary algorithm-based rule-learning system) with a computational cognitive model (written in ACT-R). In this system, the learning algorithm handles reactive aspects of the task and provides an adaptation mechanism, while the cognitive model handles cognitive aspects of the task and ensures the realism of the behavior. In this study, the controller architecture is used to implement a controller for a team of micro-air vehicles performing reconnaissance and surveillance.