Ontologies for fault-tolerant multi-agent systems

该研究计划的重点是多智能体系统的互操作性。多代理系统互操作性意味着代理应该能够相互理解。每个代理人都有一种精神状态，在这种状态下，它存储了良好运作所需的信息。因此，智能体必须能够在它们的精神状态之间交换信息。然而，在每个代理中，信息不能以相同的方式描述。因此，代理应该引用相同的词汇表，以便将接收到的信息与他们自己对该信息的描述进行映射。这个词汇表被称为本体论。本体是一种词汇表，用于引用在特定领域中操作的概念。此外，可能有几个多代理系统，其中有代理必须彼此交互。如果有至少一个本体定义为每个多智能体系统，那么我们面临的问题，集成多个本体相关的多个多智能体系统。因此，在多智能体系统需要互操作性的背景下，本研究计划提出：1）基于代理所处的上下文、代理必须响应的事件以及代理必须执行的动作来定义开发用于多代理系统的本体的方法，2）通过识别将被映射的概念来开发用于本体映射的新技术，以及它们将如何被映射，3）开发将容易识别本体的共同和不同概念的方法，4）提出用于合并本体和在合并本体时检测不一致性的新算法。

This research program focuses on multi-agent systems interoperability. Multi-agent systems interoperability means that agents should be able to understand each other. Each agent has a mental state in which it stores the information required for its well functioning. Hence, agents must be able to exchange information between their mental states. However, information could not be described by the same way in each agent. Consequently, agents should refer to a same vocabulary in order to map received information with their own description of that information. This vocabulary is called an ontology. An ontology is a vocabulary used to refer to concepts manipulated in a particular domain. Furthermore, there could be several multi-agent systems in which there are agents which have to interact with each other. If there is at least one ontology defined for each multi-agent system, then we face the problem of integrating several ontologies related to several multi-agent systems. Consequently, in the context where multi-agent systems require interoperability, this research program proposes: 1)to define a methodology to develop ontologies for multi-agent systems based on the context in which agents are, the events to which the agents must respond, and the actions the agents has to perform, 2) to develop new techniques for ontologies mapping by identifying the concepts that will be mapped, and how they will be mapped, 3)to develop approaches which will ease the identification of common and different concepts of ontologies, 4)to propose new algorithms for merging ontologies and detecting inconsistencies when merging ontologies.