Alle Publikationen
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2019
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(2019): Interactional Moral Systems: A Model of Social Mechanisms for the Moral Regulation of Exchange Processes in Agent Societies. In: IEEE Transactions on Computational Social Systems 6 (4), S. 778-796. DOI: 10.1109/TCSS.2019.2926950
DOI: https://doi.org/10.1109/TCSS.2019.2926950 Abstract: In this paper, we first introduce the concepts of moral agent and moral system of agent society and, in particular, the central concept of moral agent sensible to moral sanction. Next, we introduce the concepts of moral gain and moral loss in social exchanges and of reputation-based persistence of exchange processes. Following, we elaborate the notion of negotiated moral regulation of reputation-based persistent exchange processes. Finally, we combine those concepts in the notion of a reputation-based mechanism for the negotiation-driven moral regulation of exchange processes of agents that are sensible to moral sanctions.
Keywords: Agent societies, agent society, Avatars, Computational modeling, Ethics, ieee xplore, interactional moral systems, Law, Moral & Ethik, moral agent, moral gain, moral loss, moral regulation of social exchanges, moral sanction, Morality, multi-agent systems, negotiation-driven moral regulation, reputation-based mechanism, reputation-based persistence, reputation-based persistent exchange processes, Robots, social exchanges, social mechanisms, Social Processes 2018
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(2018): The role of a "common is moral" heuristic in the stability and change of moral norms. In: Journal of experimental psychology. General 147 (2), S. 228-242. DOI: 10.1037/xge0000365
DOI: http://www.ncbi.nlm.nih.gov/pubmed/28891657 Abstract: Moral norms are fundamental for virtually all social interactions, including cooperation. Moral norms develop and change, but the mechanisms underlying when, and how, such changes occur are not well-described by theories of moral psychology. We tested, and confirmed, the hypothesis that the commonness of an observed behavior consistently influences its moral status, which we refer to as the common is moral (CIM) heuristic. In 9 experiments, we used an experimental model of dynamic social interaction that manipulated the commonness of altruistic and selfish behaviors to examine the change of peoples' moral judgments. We found that both altruistic and selfish behaviors were judged as more moral, and less deserving of punishment, when common than when rare, which could be explained by a classical formal model (social impact theory) of behavioral conformity. Furthermore, judgments of common versus rare behaviors were faster, indicating that they were computationally more efficient. Finally, we used agent-based computer simulations to investigate the endogenous population dynamics predicted to emerge if individuals use the CIM heuristic, and found that the CIM heuristic is sufficient for producing 2 hallmarks of real moral norms; stability and sudden changes. Our results demonstrate that commonness shapes our moral psychology through mechanisms similar to behavioral conformity with wide implications for understanding the stability and change of moral norms. (PsycINFO Database Record zitiert von: 1
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(2018): Extension of grounding mechanism for abstract words: Computational methods insights. In: Artificial Intelligence Review 50 (3), S. 467-494. DOI: 10.1007/s10462-017-9608-9
DOI: https://doi.org/10.1007/s10462-017-9608-9 Abstract: The attempts to model cognitive phenomena effectively have split the research community in two paradigms: symbolic and connectionist. The extension of grounding phenomenon for abstract words is very important for social interactions of cognitive robots in real scenarios. This paper reviews the strength of symbolic and connectionist methods to address the abstract word grounding problem in cognitive robots. In particular, the presented work is focused on designing and simulating cognitive robotics model to achieve a grounding mechanism for abstract words by using the semantic network approach, as well as examining the utility of connectionist computation for the same problem. Two neuro-robotics models based on feed forward neural network and recurrent neural network are presented to see the pros and cons of connectionist approach. The simulation results and review of attributes of these methods reveal that the proposed symbolic model offers the solution to the problem of grounding abstract words with attributes like high data storage capacity with recall accuracy, structural integrity and temporal sequence handling. Whereas, connectionist computation based solutions give more natural solution to this problem with some shortcomings that include combinatorial ambiguity, low storage capacity and structural rigidity. The presented results are not only important for the advancement in communication system of cognitive robot, also provide evidence for embodied nature of abstract language. (PsycINFO Database Record (c) 2019 APA, all rights reserved)
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(2018) : Moral robots In: Johnson, L. Syd M.; Rommelfanger, Karen S. (Hg.): The Routledge handbook of neuroethics: New York, NY: Routledge/Taylor & Francis Group (Routledge handbooks in applied ethics), S. 363-377
Abstract: The main reason for raising the question about the ethical behavior of robots is the rapid progress in the development of autonomous social robots that are specifically created to be deployed in sensitive human environments, from elder and health care settings to law enforcement and military contexts. Clearly, such tasks and environments are very different from traditional factory environments (for example, for welding robots). Hence, these new social robots will require higher degrees of autonomy (i.e., a capacity for independent, self-directed action) and decision-making than any previously developed machine, given that they will face a much more complex, open world. They might be required to acquire new knowledge on the fly to accomplish a never-before-encountered task. Moreover, they will likely face humans who are not specifically trained to interact with them, and robots thus need to be responsive to instructions by novices and feel ’natural’ to humans even in unstructured interactions. At these levels of autonomy and flexibility in near-future robots, there will be countless ways in which robots might make mistakes, violate a user’s expectations and moral norms, or threaten the user’s physical or psychological safety. These social robots must therefore also be moral robots. Thus, for autonomous social robots deployed in human societies, three key questions arise: (1) What moral expectations do humans have for social robots? (2) What moral competence can and should such robots realize? (3) What should be the moral standing of these machines (if any)? The first question, about moral expectations, follows from the well-established fact that autonomous social robots, especially those with natural-language abilities, are treated in many ways like humans, regardless of whether such treatment was intended or anticipated by the robot designers. In fact, there is mounting evidence that humans have very clear expectations of robot capacities based on the robot’s appearance and people’s perceptions of the robot behaviors. We will review some of this work in the third section. The second question, about moral competence, arises from the need to endow robots with sufficient capacities to operate safely in human societies. Answers to this question would ideally build on answers to the first question and provide mechanisms for robots to process social and moral norms in ways that humans expect. In addition, the design of the robots’ control systems should ensure that robots behave ethically according to the norms of the society in which they are deployed. In this chapter, we will focus on the first two questions, discussing both human expectations and computational architectural mechanisms that will allow robots to live up to those expectations while leaving a detailed discussion of the third question to legal experts and philosophers We will not focus on the philosophical debate about agency and personhood. Rather, we will assume an operational behavioral definition of a ’moral robot’. (PsycINFO Database Record (c) 2019 APA, all rights reserved)
2016
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(2016): Computational models of development, social influences. In: Current Opinion in Behavioral Sciences 7, S. 95-100. DOI: 10.1016/j.cobeha.2015.12.008
Abstract: In the article we argue that past Bayesian approaches that model children's learning from data are missing an important element—the role of other people in generating that data. We propose that children take the origin of data into account when learning, which can be understood through ideal observer analyses of the social situation. Moreover, when observing evidence, children are not just learning from others, but also about others. We review recent literature suggesting that children can make inferences about the knowledge and goals of the individual selecting the data and use this knowledge to bolster learning from this evidence. (PsycINFO Database Record (c) 2016 APA, all rights reserved) zitiert von 4
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(2016) : Incorporating perception uncertainty in human-aware navigation: A comparative study: 2016 25th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN): New York City, USA: IEEE, S. 570-577
DOI: https://doi.org/10.1109/ROMAN.2016.7745175 Abstract: In this work, we present a novel approach to human-aware navigation by probabilistically modelling the uncertainty of perception for a social robotic system and investigating its effect on the overall social navigation performance. The model of the social costmap around a person has been extended to consider this new uncertainty factor, which has been widely neglected despite playing an important role in situations with noisy perception. A social path planner based on the fast marching method has been augmented to account for the uncertainty in the positions of people. The effectiveness of the proposed approach has been tested in extensive experiments carried out with real robots and in simulation. Real experiments have been conducted, given noisy perception, in the presence of single/multiple, static/dynamic humans. Results show how this approach has been able to achieve trajectories that are able to keep a more appropriate social distance to the people, compared to those of the basic navigation approach, and the human-aware navigation approach which relies solely on perfect perception, when the complexity of the environment increases. Accounting for uncertainty of perception is shown to result in smoother trajectories with lower jerk that are more natural from the point of view of humans.
Keywords: Angemessen(heit) (von Technik), Computational modeling, Detectors, dynamic humans, fast marching method, human-aware navigation, human-robot interaction, ieee xplore, Mobile robots, Navigation, noisy perception, path planning, perception uncertainty, Probabilistic logic, probabilistic modelling, Probability, Proposals, Robots, social costmap, social navigation performance, social path planner, social robotic system, static humans, trajectories, trajectory control, uncertain systems, uncertainty, uncertainty factor -
(2016): Computational Analysis and Simulation of Empathic Behaviors. A Survey of Empathy Modeling with Behavioral Signal Processing Framework. In: Current psychiatry reports 18 (5). DOI: 10.1007/s11920-016-0682-5
DOI: https://doi.org/10.1007/s11920-016-0682-5 Abstract: Empathy is an important psychological process that facilitates human communication and interaction. Enhancement of empathy has profound significance in a range of applications. In this paper, we review emerging directions of research on computational analysis of empathy expression and perception as well as empathic interactions, including their simulation. We summarize the work on empathic expres- sion analysis by the targeted signal modalities (e.g., text, au- dio, and facial expressions). We categorize empathy simula- tion studies into theory-based emotion space modeling or application-driven user and context modeling. We summarize challenges in computational study of empathy including con- ceptual framing and understanding of empathy, data availability, appropriate use and validation of machine learn- ing techniques, and behavior signal processing. Finally, we propose a unified view of empathy computation and offer a series of open problems for future research.
2015
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(2015) : A model of empathy to shape trolley problem moral judgements: 2015 International Conference on Affective Computing and Intelligent Interaction (ACII): Xian, China: IEEE, S. 112-118
DOI: https://doi.org/10.1109/ACII.2015.7344559 Abstract: Moral judgements are a complex phenomenon that have gained a renewed interest in the research community. Many have proposed explanations for moral judgements, including utilitarian accounts and the Principle of Double Effect. Some also advocate for the critical role of emotional processes like empathy. However, developing a computational model of moral judgements is rare perhaps due in part to the numerous influences on it. We present here a computational model of moral judgements based on moral expectation and the Principle of Double Effect. We then extend this model to provide a plausible explanation for the effect of empathy on these judgements. We evaluate these models using results from recent studies with human participants.
Keywords: Cognition, Complexity theory, computational model, Computational modeling, Decision Making, Decision theory, double effect principle, Empathy, empathy model, Ethics, ieee xplore, Moral & Ethik, moral expectation, Moral judgment, PSYCHOLOGY, shape trolley problem moral judgements, Trajectory, utility 2011
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(2011): Computational meta-ethics: Towards the meta-ethical robot. In: Minds and Machines: Journal for Artificial Intelligence, Philosophy and Cognitive Science 21 (2), S. 261-274. DOI: 10.1007/s11023-011-9229-z
DOI: https://doi.org/10.1007/s11023-011-9229-z Abstract: [Correction Notice: An erratum for this article was reported in Vol 21(3) of Minds and Machines (see record [rid]2011-14510-008[/rid]). In the original article, there was en error under the section heading ’Design of a Meta-Ethical Robot’. The correction is given in the erratum.] It has been argued that ethically correct robots should be able to reason about right and wrong. In order to do so, they must have a set of do’s and don’ts at their disposal. However, such a list may be inconsistent, incomplete or otherwise unsatisfactory, depending on the reasoning principles that one employs. For this reason, it might be desirable if robots were to some extent able to reason about their own reasoning—in other words, if they had some meta-ethical capacities. In this paper, we sketch how one might go about designing robots that have such capacities. We show that the field of computational meta-ethics can profit from the same tools as have been used in computational metaphysics. (PsycINFO Database Record (c) 2019 APA, all rights reserved)
2010
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(2010) : Moralische Gefühle aus der Sicht der kognitiv-motivationalen Theorie der Emotion In: Iorio, Marco: Regel, Norm, Gesetz: Eine interdisziplinäre Bestandsaufnahme: Frankfurt am Main [u.a.]: Lang, S. 257-283
Abstract: Vor dem Hintergrund der kognitiv-motivationalen Theorie der Emotion (KMTE) werden die Entstehung und das Wesen von moralischen Gefühlen erörtert und am Beispiel von Mitleid und Schuld vertieft. Nach einer Einführung in die kognitiv-motivationale Theorie der Emotion wird darauf aufbauend ein komputationales Modell der Emotion vorgestellt, in dem eine kognitive Architektur für Überzeugungen und Wünsche in die Analyse von Emotionen einbezieht. Das Glaube-Wunsch-System der KMTE wird in dem Modell um angeborene, festverdrahtete Überwachungs- und Aktualisierungsmechanismen erweitert, die das zentrale Repräsentationssystem überprüfen. Die Anwendung dieses Modells bei der Analyse von moralischen Emotionen wird am Beispiel des Mitleids illustriert. Neben dem kognitiv-motivationalen Hintergrund werden Sympathie- und Antipathiegefühle und das intentionale Objekt des Mitleids betrachtet. Anschließend wird die Analyse normbasierter Gefühle am Beispiel der Schuld skizziert. Abschließend werden Funktionen der moralischen Gefühle aus der Sicht des komputationalen Modells der Emotion erörtert. zitiert von: 11
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(2010): A conceptual and computational model of moral decision making in human and artificial agents. In: Topics in cognitive science 2 (3), S. 454-485. DOI: 10.1111/j.1756-8765.2010.01095.x
DOI: https://doi.org/10.1111/j.1756-8765.2010.01095.x Abstract: Recently, there has been a resurgence of interest in general, comprehensive models of human cognition. Such models aim to explain higher‐order cognitive faculties, such as deliberation and planning. Given a computational representation, the validity of these models can be tested in computer simulations such as software agents or embodied robots. The push to implement computational models of this kind has created the field of artificial general intelligence (AGI). Moral decision making is arguably one of the most challenging tasks for computational approaches to higher‐order cognition. The need for increasingly autonomous artificial agents to factor moral considerations into their choices and actions has given rise to another new field of inquiry variously known as Machine Morality, Machine Ethics, Roboethics, or Friendly AI. In this study, we discuss how LIDA, an AGI model of human cognition, can be adapted to model both affective and rational features of moral decision making. Using the LIDA model, we will demonstrate how moral decisions can be made in many domains using the same mechanisms that enable general decision making. Comprehensive models of human cognition typically aim for compatibility with recent research in the cognitive and neural sciences. Global workspace theory, proposed by the neuropsychologist Bernard Baars (1988), is a highly regarded model of human cognition that is currently being computationally instantiated in several software implementations. LIDA (Franklin, Baars, Ramamurthy, & Ventura, 2005) is one such computational implementation. LIDA is both a set of computational tools and an underlying model of human cognition, which provides mechanisms that are capable of explaining how an agent’s selection of its next action arises from bottom‐up collection of sensory data and top‐down processes for making sense of its current situation. We will describe how the LIDA model helps integrate emotions into the human decision‐making process, and we will elucidate a process whereby an agent can work through an ethical problem to reach a solution that takes account of ethically relevant factors. (PsycINFO Database Record (c) 2016 APA, all rights reserved)
Keywords: artificial general intelligence, Artificial intelligence, Cognition, computational model, Computational modeling, Computer Simulation, conceptual model, Decision Making, global workspace theory, Humans, intelligent agents, machine ethics, Machine morality, MODELS, Moral & Ethik, moral decision making, Morality, Morals, Psychological 2008
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(2008) : Ethical Trust and Social Moral Norms Simulation: A Bio-inspired Agent-Based Modelling Approach: 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, 2: Washington, DC, US: IEEE Computer Society, S. 245-251
DOI: https://doi.org/10.1109/WIIAT.2008.184 Abstract: The understanding of the micro-macro link is an urgent need in the study of social systems. The complex adaptive nature of social systems adds to the challenges of understanding social interactions and system feedback and presents substantial scope and potential for extending the frontiers of computer-based research tools such as simulations and agent-based technologies. In this project, we seek to understand key research questions concerning the interplay of ethical trust at the individual level and the development of collective social moral norms as representative sample of the bigger micro-macro link of social systems. We outline our computational model of ethical trust (CMET) informed by research findings from trust, machine ethics and neural science. Guided by the CMET architecture, we discuss key implementation ideas for the simulations of ethical trust and social moral norms.
Keywords: Adaptive systems, Agent Ensemble, Analytical models, Australia, bio-inspired agent, complex adaptive nature, computational model, Computational modeling, Computer Simulation, computer-based research tools, Context modeling, ethical aspects, ethical trust, Ethics, ieee xplore, intelligent agent, Intelligent structures, micromacro link, Moral & Ethik, moral norms, Object oriented modeling, research questions, Social interactions, social moral norms simulation, social sciences 2005
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(2005) : Human perspective on affective robotic behavior: a longitudinal study: 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems: Edmonton, AB, Canada, 2-6 August 2005: 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems: Edmonton, Alta., Canada: 8/2/2005 - 8/2/2005. IEEE/RSJ International Conference on Intelligent Robots and Systems; Institute of Electrical and Electronics Engineers: Piscataway, N.J: IEEE Operations Center, S. 1444-1451
Abstract: Humans are inherently social creatures, and affect plays no small role in their social nature. We use our emotional expressions to communicate our internal state, our moods assist or hinder our interactions on a daily basis, we constantly form lasting attitudes towards others, and our personalities make us uniquely predisposed to perform certain tasks. In this paper, we present a framework under development that combines these four areas of affect to influence robotic behavior, and describe initial results of a longitudinal human-robot interaction study. The study was designed to inform the development of the framework in order to increase ease and pleasantness of human-robot interaction.
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