Commentary :
Relying upon machine intelligence with reductions in the
supervision of human beings requires us to be able to count on a certain
level of ethical behavior from it. Formalizing ethical theories is one of the
plausible ways to add ethical dimensions to machines. Rule-based and
consequence-based ethical theories are proper candidates for Machine
Ethics. It is debatable that methodologies for each ethical theory separately
might result in an action that is not always justifiable by human
values. This inspires us to combine the reasoning procedure of two ethical
theories, deontology and utilitarianism, in a utilitarian-based deontic
logic which is an extension of STIT (Seeing To It That) logic. We keep
the knowledge domain regarding the methodology in a knowledge base
system called IDP. IDP supports inferences to examine and evaluate the
process of ethical decision making in our formalization. To validate our
proposed methodology we perform a Case Study for some real scenarios
in the domain of robotics and automatous agents.
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