基于情境演算的机器伦理学认知推理

M. Pagnucco, D. Rajaratnam, Raynaldio Limarga, Abhaya C. Nayak, Yang Song
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引用次数: 4

摘要

随着自动驾驶汽车和社交机器人等自动机器的快速发展,人们越来越意识到机器伦理对于自动机器的广泛接受至关重要。我们的目标是将道德推理编码为遵循明确定义的道德原则和行为规范的自主机器。我们提供了一种包含道德考虑的行为推理方法。它建立在Scherl和Levesque[29,30]的情境演算知识方法的基础上。我们展示了如何在动态环境中对知识进行推理,以指导伦理和道德选择,并与结果主义和义务论的伦理方法保持一致。我们将我们的方法应用于自动驾驶和社交机器人场景,并提供了一个实现框架。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Epistemic Reasoning for Machine Ethics with Situation Calculus
With the rapid development of autonomous machines such as selfdriving vehicles and social robots, there is increasing realisation that machine ethics is important for widespread acceptance of autonomous machines. Our objective is to encode ethical reasoning into autonomous machines following well-defined ethical principles and behavioural norms. We provide an approach to reasoning about actions that incorporates ethical considerations. It builds on Scherl and Levesque's [29, 30] approach to knowledge in the situation calculus. We show how reasoning about knowledge in a dynamic setting can be used to guide ethical and moral choices, aligned with consequentialist and deontological approaches to ethics. We apply our approach to autonomous driving and social robot scenarios, and provide an implementation framework.
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