Non-monotonic Reasoning for Machine Ethics with Situation Calculus

Raynaldio Limarga, Maurice Pagnucco, Yang Song, Abhaya Nayak

Abstract: With the rapid growth in research on and development of autonomous machines, machine ethics, which used to be “just a theory”, has gained greater practical importance. In this paper, we present a logical approach to machine ethics. Our objective is to enable autonomous machines to behave in morally appropriate ways following well-defined ethical principles, exercising sound ethical judgement. Since moral reasoning involves selecting appropriate behavioural actions with varying preconditions, we propose a non-monotonic reasoning model and encode the model through two types of well-known ethical frameworks: the consequentialist approach to ethics and the deontological approach to ethics. The computational model is developed using Answer Set Programming in a situation calculus framework. We apply our model to a few paradigmatic scenarios that can be encountered in autonomous driving and interactions with social robots. Our study shows that the proposed model is applicable to a wide range of scenarios and leads to appropriately different reasoning outputs in different ethical frameworks.