ATOME : a blackboard architecture with temporal and hypothetical reasoning

Abstract

To cope with high level AI-based applications as signal understanding, process control or decision making, an AI system must take into account various knowledge sources and reasoning schemes. In this paper, we propose a blackboard-based architecture which achieves opportunism and efficiency while controlling multiple knowledge sources. In addition it integrates temporal and hypothetical reasoning to deal with applications evolving in time, and manipulating noisy or errorfull information

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