Testing multi-agent systems for unwanted behavior

测试多代理系统是否存在不良行为

• 批准号: 238831-2010
• 负责人: Denzinger, Jörg
• 金额: $ 1.46万
• 依托单位: University of Calgary
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=570502
• 关键词: Testing; multi; agent; systems; unwanted

Computer systems that adapt themselves or interact with other systems provide new challenges to software testing methods. While such systems offer the possibility for more autonomy (and less need for human administration) and the possibility for emergent behaviors that provide abilities that are not possible for a single system, these same possibilities can also result in negative and unexpected effects. A system might adapt in the wrong way, or we might have emergent misbehavior when several systems try to interact with each other. This research proposal is about new testing methods that are able to find such unwanted behavior of a system or a group of systems (a multi-agent system). This will help to ensure that we can make use of the advantages of multi-agent systems without special safety concerns. In contrast to "conventional" testing methods that test if a system shows the right response in given scenarios, our testing method is able to find scenarios in which a system is showing an unwanted behavior. Using our approach, we were already successful in finding unwanted behavior in the FIFA-99 soccer game (namely user actions that always resulted in scoring a goal against the computer player), in a group of rescue agents written by students in a multi-agent system class (namely creating behaviors of agents interacting with the students' agents in such a manner that the students' agents froze), and in harbour patrol and interception policies (namely behaviors for terrorist boats that resulted in them achieving a given objective despite the defenders correctly following the policies). With the proposed research program, we investigate extensions to our basic method that expand our basic process to allow for the introductions of subgoals, that allow the integration of various knowledge about testing, the application area and the tested system, and that create the possibility to have previous test runs influence the next test run. This research will enable us to develop an extended general framework for testing multi-agent systems for multi-agent specific problems together with guidelines on how to instantiate this framework for concrete multi-agent systems.

自适应或与其他系统交互的计算机系统对软件测试方法提出了新的挑战。虽然这样的系统提供了更多的自主性（以及更少的人类管理需求）和紧急行为的可能性，这些行为提供了单一系统无法实现的能力，但这些可能性也会导致负面和意想不到的影响。一个系统可能会以错误的方式适应，或者当几个系统试图相互作用时，我们可能会出现紧急的不当行为。本研究提案是关于新的测试方法，能够发现一个系统或一组系统（多智能体系统）的这种不必要的行为。这将有助于确保我们可以利用多代理系统的优势，而无需特别的安全问题。 与测试系统在给定场景中是否显示正确响应的“传统”测试方法相比，我们的测试方法能够找到系统显示不需要的行为的场景。使用我们的方法，我们已经成功地在FIFA-99足球比赛中找到了不想要的行为（即总是导致对计算机玩家进球的用户操作），在多代理系统类中由学生编写的一组救援代理中，（即以学生代理冻结的方式创建代理与学生代理交互的行为），以及港口巡逻和拦截政策（即恐怖主义船只的行为，尽管防御者正确地遵循了政策，但仍导致他们实现了既定目标）。与建议的研究计划，我们调查扩展我们的基本方法，扩展我们的基本过程，允许引入子目标，允许集成各种知识的测试，应用领域和测试系统，并创建可能性，有以前的测试运行影响下一个测试运行。这项研究将使我们能够开发一个扩展的通用框架，用于测试多代理系统的多代理的具体问题，以及如何实例化这个框架的具体多代理系统的指导方针。