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Reasoning about Trust and Belief in Possibilistic Answer Set Programming

机译：可能性答案集编程中关于信任和信念的推理

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The Possibilistic Answer Set Framework was conceived to deal with not only non monotonic reasoning, but also with uncertainty by associating a certainty level to each piece of knowledge. Here we extend this formalism to a multiagent approach robust enough to manage both the uncertainty about autonomous agents expressed in terms of degrees of trust and the possibilistic uncertainty about their knowledge bases expressed as possibilistic answer set programs. As result, we have a decentralized system able to reason about trust and beliefs in an integrated way. Then we motivate its behavior on an example and highlight how our proposal can be employed to make decisions when the information is distributed, uncertain, potentially contradictory and not necessarily reliable.
机译：设想可能性答案集框架不仅通过将确定性级别与每条知识相关联来处理非单调推理，而且还可以处理不确定性。在这里，我们将这种形式主义扩展到一种多代理方法，该方法足够健壮，可以管理以信任度表示的自治代理的不确定性和以可能的答案集程序表示的其知识库的可能的不确定性。结果，我们有了一个去中心化的系统，该系统能够以集成方式推理信任和信念。然后，我们通过一个示例来激发其行为，并强调当信息分散，不确定，潜在矛盾且不一定可靠时，如何利用我们的建议来做出决策。

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