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Title:
Modelling Morality with Prospective Logic
Publication date:
October 2009
Citation:
moral-ijris09
Abstract:
Moral decisions can be drawn computationally by using prospective logic programs. These are employed to model moral dilemmas, as they are able to prospectively look ahead at the consequences of hypothetical moral judgments. With this knowledge of consequences, moral rules are used to decide the appropriate judgments. The whole moral reasoning is achieved via a priori constraints and a posteriori preferences on abductive stable models, two features available in prospective logic programming. We model moral dilemmas taken from the classic trolley problem and employ the principle of double effect as the moral rule. Our experiments show that preferred moral decisions, i.e. those following the principle of double effect, are delivered. We consider another moral principle, of triple effect, in our implementation. We show our prospective logic programs allow us to explain computationally different moral judgments that are drawn from these two slightly but distinctively different principles.
Journal
Authors:
Luís Moniz Pereira
,
Ari Saptawijaya
Journal:
International Journal of Reasoning-based Intelligent Systems (IJRIS)
Publisher:
Inderscience
Address:
http://www.inderscience.com/browse/index.php?journalCODE=ijris
Volume:
1
Number:
3/4
Pages:
209-221
ISBN:
1755-0556
ISSN:
-
Note:
-
Url address:
http://centria.di.fct.unl.pt/~lmp/publications/online-papers/ijris09-moral.pdf
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Plain text:
Luís Moniz Pereira and Ari Saptawijaya, Modelling Morality with Prospective Logic, International Journal of Reasoning-based Intelligent Systems (IJRIS), Vol. 1, No. 3/4, Pag. 209-221, Inderscience, http://www.inderscience.com/browse/index.php?journalCODE=ijris, ISBN 1755-0556, (http://centria.di.fct.unl.pt/~lmp/publications/online-papers/ijris09-moral.pdf), October 2009.
HTML:
<b><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>, <u>Modelling Morality with Prospective Logic</u>, International Journal of Reasoning-based Intelligent Systems (IJRIS), Vol. 1, No. 3/4, Pag. 209-221, Inderscience, http://www.inderscience.com/browse/index.php?journalCODE=ijris, ISBN 1755-0556, (<a href="http://centria.di.fct.unl.pt/~lmp/publications/online-papers/ijris09-moral.pdf" target="_blank">url</a>), October 2009.
BibTeX:
@article {moral-ijris09, author = {Lu\'{\i}s Moniz Pereira and Ari Saptawijaya}, title = {Modelling Morality with Prospective Logic}, journal = {International Journal of Reasoning-based Intelligent Systems (IJRIS)}, publisher = {Inderscience}, address = {http://www.inderscience.com/browse/index.php?journalCODE=ijris}, volume = {1}, number = {3/4}, pages = {209-221}, isbn = {1755-0556}, url = {http://centria.di.fct.unl.pt/~lmp/publications/online-papers/ijris09-moral.pdf}, abstract = {Moral decisions can be drawn computationally by using prospective logic programs. These are employed to model moral dilemmas, as they are able to prospectively look ahead at the consequences of hypothetical moral judgments. With this knowledge of consequences, moral rules are used to decide the appropriate judgments. The whole moral reasoning is achieved via a priori constraints and a posteriori preferences on abductive stable models, two features available in prospective logic programming. We model moral dilemmas taken from the classic trolley problem and employ the principle of double effect as the moral rule. Our experiments show that preferred moral decisions, i.e. those following the principle of double effect, are delivered. We consider another moral principle, of triple effect, in our implementation. We show our prospective logic programs allow us to explain computationally different moral judgments that are drawn from these two slightly but distinctively different principles.}, keywords = {modelling moral reasoning; computational morality; abductive stable models; prospective logic; ACORDA}, month = {October}, year = {2009}, }
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