【作者】 杨善林； 罗贺； 胡小建；

【Author】 YANG Shan-lin, LUO He, HU Xiao-jian (School of Computer & Information, Hefei University of Technology, Hefei 230009 China) (Institute of Computer and Network Systems, Hefei University of Technology, Hefei 230009 China) (Material Department of Science and Engineering, Hefei University of Technology, Hefei 230009 China)

【机构】 合肥工业大学计算机与信息学院； 合肥工业大学计算机网络系统研究所；

【摘要】 为了实现Agent灵活、自主的运行,Agent必须具有很强的学习能力。在BDI模型基础上,引入Q学习方法调整Agent的动作策略。提出了基于Q学习的自主Agent模型,给出了模型的结构及形式化描述,分析了Agent 的学习过程。以方格世界的搜索问题为例,验证了模型的正确性和有效性。更多还原

【Abstract】 Agent is characterized by autonomy, reactivity, sociality, and activity. As an autonomous individual, agent has the ability to control self-behaviors and self-status through learning from the environment. Q-Learning has been introduced to the traditional model of BDI, and the paper suggests an autonomous agent model based on Q-Learning, describes the structure and formalized description of the suggested model, analyzes the processing of Q-Learning in the model. Through the experiment of searching in the grid world, it indicates the validity of the suggested model and the learning ability of the agent.更多还原