Alle Publikationen
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2009
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(2009) : An artificial neural network approach for creating an ethical artificial agent: 2009 IEEE International Symposium on Computational Intelligence in Robotics and Automation - (CIRA): Daejeon, Korea: IEEE, S. 290-295
DOI: https://doi.org/10.1109/CIRA.2009.5423190 Abstract: Autonomous robotic systems and intelligent artificial agents’ capability have advanced dramatically. Since the intelligent artificial agents have been developing more autonomous and human-like, the capability of them to make moral decisions becomes an important issue. In this work we developed an artificial neutral network which considered various effective factors for ethical assessment of an action to determine that if a behavior or an action is ethically permissible or not. We integrated this net to the BDI-agent model as a part of its reasoning process to behave ethically in various environments.
Keywords: AMA, Artificial ethical agent, Artificial intelligence, artificial neural network, artificial neural network approach, artificial neural networks, autonomous robotic systems, BDI-Agent, BDI-agent model, ethical artificial agent, ethical reasoning, Ethics, Humanoid Robots, Humans, ieee xplore, intelligent agent, intelligent artificial agents, intelligent robots, Intelligent Systems, machine ethics, Mobile robots, Moral & Ethik, multi-agent systems, neurocontrollers, reasoning process, Software agents, Turning 2008
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(2008): On the design of neuro-controllers for individual and social learning behaviour in autonomous robots. An evolutionary approach. In: Connection Science 20 (2-3), S. 211-230. DOI: 10.1080/09540090802092014
Abstract: In biology/psychology, the capability of natural organisms to learn from the observation/interaction with conspecifics is referred to as social learning. Roboticists have recently developed an interest in social learning, since it might represent an effective strategy to enhance the adaptivity of a team of autonomous robots. In this study, we show that a methodological approach based on artifcial neural networks shaped by evolutionary computation techniques can be successfully employed to synthesise the individual and social learning mechanisms for robots required to learn a desired action (i.e. phototaxis or antiphototaxis).
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