Computational Agent Responsibility

工程系统正变得越来越复杂，越来越自治。一旦他们被允许，甚至被要求，做出自己的决定，一系列关于安全，道德和可信度的问题就会浮出水面。用户不太可能相信这些系统，而监管机构不太可能甚至允许他们的部署，没有强有力的证据，自主系统可以作出的决定，以及随后的行动，他们可以take. We的工作，自主系统的混合代理体系结构的发展和分析表明，如何强大的（正式）验证可以进行后，在一个合适的方式构建的系统的核心决策。我们的方法也被用来捕捉和验证自治系统可能做出的某些“道德”决定，当系统在不可预见的情况下面临关键决定时，这些决定尤其重要，并且必须决定好/坏的行动。然而，很明显，简单版本的道德原则，如好/坏或对/错，我们需要在实践中加强“责任”概念。这些问题在哲学中得到了很好的研究，尽管主要是通过人类道德或法律的责任的透镜。在这个项目中，我们的目标是确定和开发合适的概念的“责任”，这是从哲学的观点一致，但也可以在计算代理在我们的自治系统的核心使用。在这样做的过程中，我们为责任的正式验证，复杂的解释，以及至关重要的是，使用责任作为代理决策和行动的驱动因素铺平了道路。因此，我们的中心目标是设计一个框架，自治系统的责任，是合理的，有效的实施，并在实践中验证。

Engineered systems are becoming more complex and, increasingly, more autonomous. Once they are allowed, or even required, to make their own decisions a wide range of issues concerning safety, ethics and trustworthiness come to the fore. Users are unlikely to trust these systems while regulators are unlikely to even allow their deployment without strong evidence concerning decisions that autonomous systems can make and the subsequent actions they can take.Our work on the development and analysis of hybrid agent architectures for autonomous systems has shown how strong (formal) verification can be carried out upon core decision-making in systems constructed in a suitable manner. Our approach has also been used to capture and verify certain "ethical" decisions the autonomous system might make, which are especially important when the system is confronted by critical decisions in unforeseen situations and must decide on good/bad actions.However, it has become clear that simple versions of ethical principles, such as good/bad or right/wrong, are insufficient and that we need stronger concepts of "responsibility" in practice. Such issues are well-studied in Philosophy, though mainly through the lens of human morality or legal accountability. In this project we aim to identify and develop suitable notions of "responsibility" that are consistent with views from Philosophy but that can also be used within computational agents at the heart of our autonomous systems. In doing this, we pave the way for formal verification of responsibility, sophisticated explanations and, crucially, the use of responsibilities as a driver for agent decisions and actions. Thus, our central aim is to devise a framework for autonomous systems responsibility that is philosophically justifiable, effectively implementable, and practically verifiable.