A New Architecture for Making Moral Agents Based on C4.5 Decision Tree Algorithm | Zendy

Meisam AzadManjiri | Zendy

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A New Architecture for Making Moral Agents Based on C4.5 Decision Tree Algorithm

Author(s) -

Meisam AzadManjiri

Publication year - 2014

Publication title -

international journal of information technology and computer science

Language(s) - English

Resource type - Journals

eISSN - 2074-9015

pISSN - 2074-9007

DOI - 10.5815/ijitcs.2014.05.07

Subject(s) - computer science , morality , architecture , robot , dimension (graph theory) , artificial intelligence , moral dilemma , order (exchange) , tree (set theory) , decision tree , algorithm , human–computer interaction , epistemology , mathematics , social psychology , psychology , philosophy , art , mathematical analysis , visual arts , finance , pure mathematics , economics

Regarding to the influence of robots in the various fields of life, the issue of trusting to them is important, especially when a robot deals with people directly. One of the possible ways to get this confidence is adding a moral dimension to the robots. Therefore, we present a new architecture in order to build moral agents that learn from demonstrations. This agent is based on Beauchamp and Childress's principles of biomedical ethics (a type of deontological theory) and uses decision tree algorithm to abstract relationships between ethical principles and morality of actions. We apply this architecture to build an agent that provides guidance to health care workers faced with ethical dilemmas. Our results show that the agent is able to learn ethic well.

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