DocumentCode :
3379071
Title :
A biologically inspired computational model of Moral Decision Making for autonomous agents
Author :
Cervantes, Jose-Antonio ; Rodriguez, Luis-Felipe ; Lopez, Sebastian ; Ramos, Felix
Author_Institution :
Dept. of Comput. Sci., Cinvestav, Guadalajara, Mexico
fYear :
2013
fDate :
16-18 July 2013
Firstpage :
111
Lastpage :
117
Abstract :
In areas such as psychology and neuroscience a common approach to study human behavior has been the development of theoretical models of cognition. In fields such as artificial intelligence, these cognitive models are usually translated into computational implementations and incorporated into the architectures of intelligent autonomous agents (AAs). The main assumption is that this design approach contributes to the development of intelligent systems capable of displaying very believable and human-like behaviors. Decision Making is one of the most investigated and computationally implemented cognitive functions. The literature reports several computational models designed to allow AAs to make decisions that help achieve their personal goals and needs. However, most models disregard crucial aspects of human decision making such as other agents´ needs, ethical values, and social norms. In this paper, we propose a biologically inspired computational model of Moral Decision Making (MDM). This model is designed to enable AAs to make decisions based on ethical and moral judgment. The simulation results demonstrate that the model helps to improve the believability of virtual agents when facing moral dilemmas.
Keywords :
cognition; decision making; ethical aspects; mobile agents; AA; MDM; autonomous agents; biologically inspired computational model; ethical judgment; moral decision making; moral judgment; virtual agents; Biological system modeling; Brain modeling; Computational modeling; Decision making; Ethics; Psychology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cognitive Informatics & Cognitive Computing (ICCI*CC), 2013 12th IEEE International Conference on
Conference_Location :
New York, NY
Print_ISBN :
978-1-4799-0781-6
Type :
conf
DOI :
10.1109/ICCI-CC.2013.6622232
Filename :
6622232
Link To Document :
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