S&AS: FND: A Stochastic Ethical Decision-Making Framework for Long-Term Autonomy

为了让机器人有效地与人类合作，它们必须能够对其决策和行为的伦理后果进行推理，纳入社会价值观、规则和惯例。例如，自动驾驶汽车预计将在5-10年内变得司空见惯。自动驾驶汽车将为道路安全提供许多优势，并将为那些面临物理挑战的人提供机动性。然而，要想让这类汽车取得成功，必须解决多个伦理问题。例如，在将伤者送往医院的过程中，允许汽车违反交通法规吗？如果一辆车意识到事故是不可避免的，它应该怎么做？一辆车怎么能以人类社会(和法院)可以理解和接受的方式推理呢？在将机器人应用于军事行动、执法和医疗保健等领域时，也会出现重要的伦理问题。为了解决这些问题，这项研究将为机器人提供推理和计划任务的方法，并做出符合伦理道德的决定。这些推理程序将使机器人能够随着时间的推移学习和适应法律和社会习俗的变化。该研究方法基于规范推理和马尔可夫决策过程(MDP)规划相结合，以创建一个伦理智能物理系统(IPS)，该系统将通过人体实验进行评估。这项研究的创新之处在于：(A)在长期自主的背景下，关于任务绩效和道德行为的综合推理方式，其中道德规则可以改变，行动结果可能取决于任务和背景；(B)通过考虑和解决领域目标和规范目标之间的冲突，评估机器人行动的后果的原则性方法；(C)以灵活和依赖背景的方式确定规范优先级的标准；(D)考虑规范的整个生命周期，即规范激活、停用、矛盾、违规和过时的方法。

For robots to effectively collaborate with humans, they must be able to reason about the ethical consequences of their decisions and actions, incorporating societal values, rules, and conventions. Consider, for example, autonomous cars, which are envisioned to become commonplace in 5-10 years. Autonomous cars will provide many advantages for road safety, and they will offer mobility to those with physical challenges. For such cars to be successful, however, multiple ethical problems must be solved. For example, is it allowable for a car to break traffic laws as it is taking a wounded person to a hospital? What should a car do if it recognizes that an accident is unavoidable? How can a car reason in a way that is understandable and acceptable in human society (and courts of law)? Important ethical questions also arise in applications of robotics to areas such as military engagements, law enforcement, and healthcare. To address these issues, the research will provide ways for robots to reason and plan their tasks and make ethically sound decisions. These reasoning procedures will enable robots to learn and adapt over time as laws and social conventions change. The research approach is based on normative reasoning integrated with Markov Decision Process (MDP) planning to enable the creation of an ethical intelligent Physical System (IPS) that will be evaluated via human experiments. The research is innovative in that it will provide: (a) an integrated way of reasoning about task performance and ethical behavior in the context of long-term autonomy, where ethical rules can be changing and action consequences could be task and context dependent, (b) principled ways of evaluating consequences of robot actions, by considering and resolving conflicts between domain goals and normative goals, (c) criteria to determine norm priority in a flexible and context dependent manner, (d) methods to consider the whole life-cycle of norms, namely norm activation, deactivation, contradiction, violation and obsolescence.