Non-monotonic reasoning for machine ethics with situation calculus

Raynaldio Limarga, Maurice Pagnucco, Yang Song*, Abhaya Nayak

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

2 Citations (Scopus)


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.

Original languageEnglish
Title of host publicationAI 2020: Advances in Artificial Intelligence
Subtitle of host publication33rd Australasian Joint Conference, AI 2020 Canberra, ACT, Australia, November 29–30, 2020, Proceedings
EditorsMarcus Gallagher, Nour Moustafa, Erandi Lakshika
Place of PublicationCham, Switzerland
PublisherSpringer, Springer Nature
Number of pages13
ISBN (Electronic)9783030649845
ISBN (Print)9783030649838
Publication statusPublished - 2020
Event33rd Australasian Joint Conference on Artificial Intelligence, AI 2020 - Virtual, Canberra, ACT, Australia
Duration: 29 Nov 202030 Nov 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12576 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference33rd Australasian Joint Conference on Artificial Intelligence, AI 2020
Abbreviated titleAI 2020
CityCanberra, ACT


  • Answer Set Programming
  • Machine ethics
  • Situation calculus


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