Analyzing multi-agent systems with probabilistic model checking approach
ICSE(2012)
摘要
Multi-agent systems, which are composed of autonomous agents, have been successfully employed as a modeling paradigm in many scenarios. However, it is challenging to guarantee the correctness of their behaviors due to the complex nature of the autonomous agents, especially when they have stochastic characteristics. In this work, we propose to apply probabilistic model checking to analyze multi-agent systems. A modeling language called PMA is defined to specify such kind of systems, and LTL property and logic of knowledge combined with probabilistic requirements are supported to analyze system behaviors. Initial evaluation indicates the effectiveness of our current progress; meanwhile some challenges and possible solutions are discussed as our ongoing work.
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关键词
probabilistic model checking,stochastic processes,pma,autonomous agent,complex nature,autonomous agents,stochastic characteristics,modeling paradigm,multi-agent systems,modeling language,multi-agent system,knowledge logic,current progress,ongoing work,ltl property,probabilistic requirement,probabilistic model checking approach,system behaviors,formal verification,multi agent system,multiagent systems,games,multi agent systems,semantics,cognition,probabilistic logic
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