On Real Reward Testing

作     者：杨伟忠 邓玉欣 YANG Wei-zhong DENG Yu-xin~* (MOE-MS Key Laboratory for Intelligent Computing and Intelligent Systems, Shanghai Jiaotong University,Shanghai 200240,China)

作者机构：MOE-MS Key Laboratory for Intelligent Computing and Intelligent SystemsShanghai Jiaotong University 

出 版 物：《Journal of Shanghai Jiaotong university(Science)》 (上海交通大学学报（英文版）)

年 卷 期：2011年第16卷第4期

页      面：479-484页

核心收录：

学科分类：08[工学] 081202[工学-计算机软件与理论] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：the National Natural Science Foundation of China(No.61033002) 

主　　题：probabilistic processes real reward testing nonnegative reward testing failure simulation 

摘      要：We extend the traditional nonnegative reward testing with negative *** this new testing framework,may preorder and must preorder are the inverse of each *** surprisingly,it turns out that the real reward must testing is no more powerful than the nonnegative reward testing,at least for finite processes. In order to prove that result,we exploit an important property of failure simulation about the inclusion of the testing outcomes between two related processes.