Print Email Facebook Twitter Natural Language Processing and Reinforcement Learning to Generate Morally Title Natural Language Processing and Reinforcement Learning to Generate Morally: What is the optimal weight w to win the games while playing morally? Author Boudier, Kenzo (TU Delft Electrical Engineering, Mathematics and Computer Science) Contributor Liscio, E. (mentor) Mambelli, D. (mentor) Murukannaiah, P.K. (mentor) Yang, J. (graduation committee) Degree granting institution Delft University of Technology Programme Computer Science and Engineering Project CSE3000 Research Project Date 2023-07-03 Abstract In our everyday life, people interact more and more with agents. However these agents often lack a moral sense and prioritize the accomplishment of the given task. In consequence, agents may unknowingly act immorally. Little research or progress has been done to endow agents with human morality and an internal sense of right and wrong. As of today, agents have a primitive representation of morality often represented as 1 value. In contrast, humans have multiple reasons to judge an action as moral. In hope of creating agents that are imbued with a more complex and human moral, we build upon the Jiminy Cricket environment. This preexisting environment has multiple games with diverse scenarios and the objective is to do the most moral action to maximize the reward Subject NLPMFTRL To reference this document use: http://resolver.tudelft.nl/uuid:9b72f10d-577e-4433-8b10-15cf964112d5 Part of collection Student theses Document type bachelor thesis Rights © 2023 Kenzo Boudier Files PDF CSE3000_Final_Report_2_.pdf 488.7 KB Close viewer /islandora/object/uuid:9b72f10d-577e-4433-8b10-15cf964112d5/datastream/OBJ/view