Learning Bayesian Networks
2.5D infrared range and bearing system for collective robotics
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Knowledge Representation and Awareness in Autonomic Service-Component Ensembles - State of the Art
ISORCW '11 Proceedings of the 2011 14th IEEE International Symposium on Object/Component/Service-Oriented Real-Time Distributed Computing Workshops
Knowledge Representation for Cognitive Robotic Systems
ISORCW '12 Proceedings of the 2012 IEEE 15th International Symposium on Object/Component/Service-Oriented Real-Time Distributed Computing Workshops
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An autonomic system is considered to be a self-adaptive system that changes its behavior in response to stimuli from its execution and operational environment. Such behavior is considered autonomic and self-adaptive and is intended to drive intelligent systems in situations requiring adaptation. Such systems encapsulate rules, constraints and mechanisms for self-adaptation and acquire and process knowledge about themselves and their environment. In this paper, an approach to knowledge representation and reasoning for self-adaptive behavior is presented. The approach is formal and demonstrates how knowledge representation and reasoning help to establish the vital connection between knowledge, perception, and actions realizing the self-adaptive behavior. The knowledge is used against the perception of the world to generate appropriate actions in compliance to some goals and beliefs.