实时环境下Agent决策机制研究

Studies on Decision Mechanism of Agents Based on Real-time Environment

在分析已有Agent模型的基础上,提出了一种新的实时Agent模型。这种模型将Agent的审慎型行为和反应型行为结合在一起,其效率比已有的Agent模型有较大的提高。文中还讨论了实时Agent的决策机制,提出用感知器算法对特征进行分类和任意时间算法进行决策。

This paper discusses the performance measures for real-time systems, and a real-time agent architecture is put forwarded on the basis of analyzing the existing models of agent architecture and outline the challenging issues that have to be addressed in the architecture, such as using perceptron approach in artificial neural network to classify the features of the tasks and applying anytime algorithm to decision etc. This architecture incorporates the deliberative behavior with reactive behavior together to get an effective solution. Finally this paper discusses the decision mechanism of the architecture presented in the paper and points out the future research trend of real-time AI systems.