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An MDE Approach for Modelling and Reasoning About Multi-agent Systems

机译:多主体系统建模和推理的MDE方法

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Epistemic logic plays an important role in artificial intelligence for reasoning about multi-agent systems. Current approaches for modelling multi-agent systems with epistemic logic use Kripke semantics where the knowledge base of an agent is represented as atomic propositions, but intelligent agents need to be equipped with formulas to derive implicit information. In this paper, we propose a metamodelling approach where agents' state of affairs are separated in different scopes; and the knowledge base of an agent is represented by a propositional logic language restricted to Horn clauses. We propose to use a model driven approach for the diagrammatic representation of multi-agent systems knowledge (and nested knowledge). We use a message passing for updating the state of affairs of agents and use belief revision to update the knowledge base of agents.
机译:认知逻辑在人工智能中对多智能体系统的推理起着重要作用。使用认知逻辑对多智能体系统进行建模的当前方法使用Kripke语义,其中智能体的知识库表示为原子命题,但是智能智能体需要配备公式以导出隐式信息。在本文中,我们提出了一种元模型化方法,其中代理的事务状态在不同的范围内分开。代理的知识库由仅限于Horn子句的命题逻辑语言表示。我们建议使用模型驱动的方法来表示多主体系统知识(和嵌套知识)。我们使用消息传递来更新代理的状态,并使用信念修订来更新代理的知识库。

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