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2017
Sarathy, V.; Scheutz, M.; Malle, B. F. (2017) : Learning behavioral norms in uncertain and changing contexts: 2017 8th IEEE International Conference on Cognitive Infocommunications (CogInfoCom): Debrecen, Hungary: IEEE, S. 000301-000306

DOI: https://doi.org/10.1109/CogInfoCom.2017.8268261

Abstract: Human behavior is often guided by social and moral norms. Robots that enter human societies must therefore behave in norm-conforming ways as well to increase coordination, predictability, and safety in human-robot interactions. However, human norms are context-specific and laced with uncertainty, making the representation, learning, and communication of norms challenging. We provide a formal representation of norms using deontic logic, Dempster-Shafer Theory, and a machine learning algorithm that allows an artificial agent to learn norms under uncertainty from human data. We demonstrate a novel cognitive capability with which an agent can dynamically learn norms while being exposed to distinct contexts, recognizing the unique identity of each context and the norms that apply in it.

Keywords: Artificial agent, behavioral norms, behavioural sciences computing, Cognition, Conferences, Dempster-Shafer Theory, deontic logic, Ethics, formal logic, Human behavior, human societies, human-robot interaction, human-robot interactions, ieee xplore, inference mechanisms, learning (artificial intelligence), Libraries, machine learning algorithm, Moral & Ethik, moral norms, norm-conforming ways, Robot kinematics, Social Norms, uncertainty, uncertainty handling
2015
Scheutz, M.; Malle, B.; Briggs, G. (2015) : Towards morally sensitive action selection for autonomous social robots: 2015 24th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN): Kobe, Japan: IEEE Robotics & Automation Society, S. 492-497

DOI: https://doi.org/10.1109/ROMAN.2015.7333661

Abstract: Autonomous social robots embedded in human societies have to be sensitive to human social interactions and thus to moral norms and principles guiding these interactions. Actions that violate norms can lead to the violator being blamed. Robots thus need to be able to anticipate possible norm violations and attempt to prevent them while they execute actions. If norm violations cannot be prevented (e.g., in a moral dilemma situation in which every action leads to a norm violation), then the robot needs to be able to justify the action to address any potential blame. In this paper, we present a first attempt at an action execution system for social robots that can (a) detect (some) norm violations, (b) consult an ethical reasoner for guidance on what to do in moral dilemma situations, and (c) it can keep track of execution traces and any resulting states that might have violated norms in order to produce justifications.

Keywords: action execution system, autonomous social robots, Cleaning, Collision avoidance, ethical aspects, ethical reasoner, Ethics, human social interactions, human societies, human-robot interaction, ieee xplore, Mobile robots, Moral & Ethik, moral dilemma situation, morally sensitive action selection, norm violations, Robot sensing systems, social aspects of automation

2017

2015

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