Aiming to the uncetainty of production enviroment in knowledgeable manufacturing system, an interoperable
knowledgeable dynamic scheduling system based on multi-agent is built, in which a knowledge representation with a series
of problem characteristics for various scheduling problems is adopted and problem-based function modules are constructed
by using agent technology. An adaptive scheduling mechanism based on modified Q-learning agrorithm known as weighted
subordination based Q-learning(WSQ) is proposed for guiding the equipment agent to select scheduling strategy in a dynamic
enviroment. By the analysis of its complexity and simulation experiments, the results show the effectiveness of this strategy.
The system is of adaptive and self-learning features, and high intelligence and interoperability.