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Publication details
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Title:
Modelling Morality with Prospective Logic
Publication date:
May 2011
Citation:
mmwpl-cup
Abstract:
We show how moral decisions can be drawn computationally by using prospective logic programs. These are employed to model moral dilemmas, being able to prospectively look ahead at the consequences of hypothetical moral judgments. With knowledge of consequences, moral rules are then used to decide the appropriate moral judgments. Moral reasoning is achieved by a priori constraints and a posteriori preferences on abductive stable models, 2 features available in prospective logic programming. We model various moral dilemmas taken from the classic trolley problem and employ the principle of double effect for moral rule. Experiments show that preferred moral decisions, those following the principle of double effect, are successfully delivered. We consider yet another moral principle, the principle of triple effect, in our implementation. We show prospective logic programs explain computationally different moral judgments drawn from these 2 different principles.
Book chapter
Authors:
Luís Moniz Pereira
,
Ari Saptawijaya
Editors:
Michael Anderson, Susan Anderson
Book title:
Machine Ethics
Series:
-
Publisher:
Cambridge University Press
Address:
http://www.cambridge.org/gb/knowledge/isbn/item6282745/?site_locale=en_GB
Volume:
-
Pages:
398-421
ISBN:
9780521112352
ISSN:
-
Note:
-
Url address:
http://centria.di.fct.unl.pt/~lmp/publications/online-papers/moral-cup.pdf
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Plain text:
Luís Moniz Pereira and Ari Saptawijaya, Modelling Morality with Prospective Logic, in: Michael Anderson and Susan Anderson (eds), Machine Ethics, Cambridge University Press, http://www.cambridge.org/gb/knowledge/isbn/item6282745/?site_locale=en_GB, ISBN 9780521112352, Pag. 398-421, (http://centria.di.fct.unl.pt/~lmp/publications/online-papers/moral-cup.pdf), May 2011.
HTML:
<a href="/people/members/view.php?code=6175f826202ff877fba2ad77784cb9cb" class="author">Luís Moniz Pereira</a> and <a href="/people/members/view.php?code=3296a2fcb759ac3f30bc313a41f955bc" class="author">Ari Saptawijaya</a>, <b>Modelling Morality with Prospective Logic</b>, in: Michael Anderson and Susan Anderson (eds), <u>Machine Ethics</u>, Cambridge University Press, http://www.cambridge.org/gb/knowledge/isbn/item6282745/?site_locale=en_GB, ISBN 9780521112352, Pag. 398-421, (<a href="http://centria.di.fct.unl.pt/~lmp/publications/online-papers/moral-cup.pdf" target="_blank">url</a>), May 2011.
BibTeX:
@incollection {mmwpl-cup, author = {Lu\'{\i}s Moniz Pereira and Ari Saptawijaya}, editor = {Michael Anderson and Susan Anderson}, title = {Modelling Morality with Prospective Logic}, booktitle = {Machine Ethics}, publisher = {Cambridge University Press}, address = {http://www.cambridge.org/gb/knowledge/isbn/item6282745/?site_locale=en_GB}, pages = {398-421}, isbn = {9780521112352}, url = {http://centria.di.fct.unl.pt/~lmp/publications/online-papers/moral-cup.pdf}, abstract = {We show how moral decisions can be drawn computationally by using prospective logic programs. These are employed to model moral dilemmas, being able to prospectively look ahead at the consequences of hypothetical moral judgments. With knowledge of consequences, moral rules are then used to decide the appropriate moral judgments. Moral reasoning is achieved by a priori constraints and a posteriori preferences on abductive stable models, 2 features available in prospective logic programming. We model various moral dilemmas taken from the classic trolley problem and employ the principle of double effect for moral rule. Experiments show that preferred moral decisions, those following the principle of double effect, are successfully delivered. We consider yet another moral principle, the principle of triple effect, in our implementation. We show prospective logic programs explain computationally different moral judgments drawn from these 2 different principles.}, keywords = {Modelling moral reasoning; computational morality; abductive stable models; prospective logic; ACORDA}, month = {May}, year = {2011}, }
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