Alle Publikationen
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2016
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(2016): Towards assessing the human trajectory planning horizon. In: PLoS one 11 (12)
Abstract: Mobile robots are envisioned to cooperate closely with humans and to integrate seamlessly into a shared environment. For locomotion, these environments resemble traversable areas which are shared between multiple agents like humans and robots. The seamless integration of mobile robots into these environments requires accurate predictions of human locomotion. This work considers optimal control and model predictive control approaches for accurate trajectory prediction and proposes to integrate aspects of human behavior to improve their performance. Recently developed models are not able to reproduce accurately trajectories that result from sudden avoidance maneuvers. Particularly, the human locomotion behavior when handling disturbances from other agents poses a problem. The goal of this work is to investigate whether humans alter their trajectory planning horizon, in order to resolve abruptly emerging collision situations. By modeling humans as model predictive controllers, the influence of the planning horizon is investigated in simulations. Based on these results, an experiment is designed to identify, whether humans initiate a change in their locomotion planning behavior while moving in a complex environment. The results support the hypothesis, that humans employ a shorter planning horizon to avoid collisions that are triggered by unexpected disturbances. Observations presented in this work are expected to further improve the generalizability and accuracy of prediction methods based on dynamic models. (PsycINFO Database Record (c) 2017 APA, all rights reserved)
2014
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Bosse, Tibor; Broekens, Joost; Dias, João; van der Zwaan, Janneke (Hg.) (2014): Emotion Modeling. Towards Pragmatic Computational Models of Affective Processes. Cham: Springer International Publishing, Imprint, Springer (Lecture Notes in Computer Science)
DOI: https://doi.org/10.1007/978-3-319-12973-0 Abstract: Emotion modeling has been an active area of research for almost two decades now. In spite of the growing and diverse body of work in emotion modeling, designing and developing emotion models remains an art, with few standards and systematic guidelines available to guide the design process, and to validate the resulting models. This state-of-the-art volume includes extended versions of eight papers presented at two workshops: Standards in Emotion Modeling, SEM 2011, held in Leiden, The Netherlands, in August 2011, which focused on the challenges, progress and open questions regarding emotion modeling standards, and Emotional and Empathic Agents, EEA 2012, held in conjunction with AAMAS 2012, in Valencia, Spain, in June 2012, which focused on strategies for reducing the complexity of affective models and model re-use. The papers have been organized into two sections: generic models and frameworks, and evaluations of specific models. They represent a sampling of the current efforts toward the development of more systematic methods for emotion modeling, toward the development of standards in emotion model design and validation, and toward more pragmatic approaches to model development, including model component sharing and re-use. The topics range from efforts to define minimum functionalities for agent emotion models and provide tools for systematic comparisons of alternative approaches through approaches to integrating multiple processing levels within an agent architecture to papers exploring the best means of generating empathy and supportive behavior in virtual agents and attempts to address the requirements for realistic modeling of affective expressions across multiple types of social interaction (individual, group and cultural).
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(2014): Learning Compliant Manipulation through Kinesthetic and Tactile Human-Robot Interaction. In: IEEE Transactions on Haptics 7 (3), S. 367-380. DOI: 10.1109/TOH.2013.54
DOI: https://doi.org/10.1109/TOH.2013.54 Abstract: Robot Learning from Demonstration (RLfD) has been identified as a key element for making robots useful in daily lives. A wide range of techniques has been proposed for deriving a task model from a set of demonstrations of the task. Most previous works use learning to model the kinematics of the task, and for autonomous execution the robot then relies on a stiff position controller. While many tasks can and have been learned this way, there are tasks in which controlling the position alone is insufficient to achieve the goals of the task. These are typically tasks that involve contact or require a specific response to physical perturbations. The question of how to adjust the compliance to suit the need of the task has not yet been fully treated in Robot Learning from Demonstration. In this paper, we address this issue and present interfaces that allow a human teacher to indicate compliance variations by physically interacting with the robot during task execution. We validate our approach in two different experiments on the 7 DoF Barrett WAM and KUKA LWR robot manipulators. Furthermore, we conduct a user study to evaluate the usability of our approach from a non-roboticists perspective.
Keywords: Algorithms, Analysis, Bedienung & Handhabung, Biomechanical Phenomena, compliance control, compliance variations, compliant control, compliant manipulation, Computer Simulation, education, Force, haptic feedback, haptic interfaces, human-robot interaction, Humans, Impedance, Joints, Kinesthesis, kinesthetic human-robot interaction, KUKA LWR robot manipulators, Learning, manipulator kinematics, Physical Human-Robot Interaction, position control, RLfD, Robot kinematics, robot learning from demonstration, Robot sensing systems, Robotics, stiff position controller, tactile human-robot interaction, tactile interfaces, task kinematics, task model, Task Performance, Touch 2013
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(2013): A Simulation of Rule-Breaking Behavior in Public Places. In: Social Science Computer Review 32 (4), S. 439-452. DOI: 10.1177/0894439313511186
DOI: https://doi.org/10.1177/0894439313511186 Abstract: A computer simulation based on both game theory and the cellular automaton model was conducted to investigate the effects of individuals’ interactions and certain conditions on the spread of rule-breaking behavior in public places. Four decision matrices representing obedient, deviant, conforming, and contrary principles were prepared experimentally. The ratio of these principles ranged from 1:2:3:4 to 4:3:2:1 (obedient:deviant:conforming:contrary). There were a total of 24 data sets with each data set composed of 10 decision matrices. In addition to these 24 data sets, the ratio 1:1:1:1 was prepared. This data set was composed of four decision matrices. The results indicated that rule-breaking behavior spreads under the following conditions: (A) when people act according to both individual factors (e.g., their attitudes) and situational factors (e.g., their neighbors’ behavior); (B) when there are more deviant people than obedient people; (C) when the intensity of ru le-break ing behavior is higher than that of rule-obeying behavior. Condition A is an important factor. If conditions B or C are satisfied, the spread of rule-breaking behavior does not occur necessarily. At a certain probability threshold, rule-breaking behavior spreads sharply when people act based on individual factors (e.g., their attitudes); the spread of such behavior cannot be attributed solely to situational factors (e.g., neighbors' behavior). There is only a fine line between rule breaking and obeying near the probability threshold. (PsycINFO Database Record (c) 2016 APA, all rights reserved) zitiert von 6
2011
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(2011): Autonome Technik als Herausforderung der soziologischen Handlungstheorie / Autonomous Technology as a Challenge to the Sociological Theory of Action. In: Zeitschrift für Soziologie 40 (2), S. 91-111. DOI: 10.1515/zfsoz-2011-0201
Abstract: Die vorliegende Abhandlung entwickelt ein soziologisches Modell, welches das „Mit-Handeln“ von Technik beschreibt und in einer Weise operationalisiert, dass die Frage der Handlungsträgerschaft empirisch untersucht werden kann. Es wird gezeigt, dass die von der Actor-Network-Theory thematisierten Phänomene auch im Rahmen einer soziologischen Handlungstheorie betrachtet werden können, die sich auf das Esser’sche Modell soziologischer Erklärung stützt. Das Ergebnis ist ein Modell soziologischer Erklärung hybrider Systeme, das die Interaktion von menschlichen Akteuren und nicht-menschlichen Aktanten beschreibt. Zu dessen Überprüfung wurden Experimente in einem selbst programmierten Fahrsimulator durchgeführt. Deren Auswertung belegt, dass die Probanden den technischen Assistenzsystemen Handlungsträgerschaft zuschreiben und das Verhältnis Mensch-Technik als ein symmetrisches wahrnehmen. Zudem tendieren sie dazu, sich je nach Handlungsverteilung der Verfolgung bestimmter Ziele zu entledigen, obwohl nach den Spielregeln „humans“ und „non-humans“ gleichermaßen für die Verfolgung aller Ziele verantwortlich waren.
Keywords: actor network theory, Actor-Network-Theory, agency, Agent-based Modelling, Agent-Based Modelling and Simulation, ANT, ANT und ANT mit Esserschem Modell, autonome Technik, Operationiliserung technischen Handelns, Autonomous Technology, Computer Simulation, Disziplin, doppelter Treffer, Esser, Experimental Sociology, Favoriten, Handlungsträgerschaft, Man-Machine Interaction, Model of Sociological Explanation, Modelle/Theorien, Soziologie, Soziologisches Handlungsmodell von Hartmut Esser, Theory of Action 2010
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(2010): "Artificial humans": Psychology and neuroscience perspectives on embodiment and nonverbal communication. In: Neural networks : the official journal of the International Neural Network Society 23 (8-9), S. 1077-1090. DOI: 10.1016/j.neunet.2010.06.003
DOI: https://doi.org/10.1016/j.neunet.2010.06.003 Abstract: "Artificial humans", so-called "Embodied Conversational Agents" and humanoid robots, are assumed to facilitate human-technology interaction referring to the unique human capacities of interpersonal communication and social information processing. While early research and development in artificial intelligence (AI) focused on processing and production of natural language, the "new AI" has also taken into account the emotional and relational aspects of communication with an emphasis both on understanding and production of nonverbal behavior. This shift in attention in computer science and engineering is reflected in recent developments in psychology and social cognitive neuroscience. This article addresses key challenges which emerge from the goal to equip machines with socio-emotional intelligence and to enable them to interpret subtle nonverbal cues and to respond to social affordances with naturally appearing behavior from both perspectives. In particular, we propose that the creation of credible artificial humans not only defines the ultimate test for our understanding of human communication and social cognition but also provides a unique research tool to improve our knowledge about the underlying psychological processes and neural mechanisms.
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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 2007
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Pelachaud, Catherine; Martin, Jean-Claude; André, Elisabeth; Chollet, Gérard; Karpouzis, Kostas; Pelé, Danielle (Hg.) (2007): Intelligent virtual agents. 7th international conference, IVA 2007, Paris, France, September 17-19, 2007: Proceedings. Iva; International Conference on Intelligent Virtual Agents. Berlin: Springer (Lecture notes in computer science Lecture notes in artificial intelligence)
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(2007): The representation of information about faces in the temporal and frontal lobes. In: Neuropsychologia 45 (1), S. 124-143. DOI: 10.1016/j.neuropsychologia.2006.04.019
DOI: http://www.ncbi.nlm.nih.gov/pubmed/16797609 Abstract: Neurophysiological evidence is described showing that some neurons in the macaque inferior temporal visual cortex have responses that are invariant with respect to the position, size and view of faces and objects, and that these neurons show rapid processing and rapid learning. Which face or object is present is encoded using a distributed representation in which each neuron conveys independent information in its firing rate, with little information evident in the relative time of firing of different neurons. This ensemble encoding has the advantages of maximising the information in the representation useful for discrimination between stimuli using a simple weighted sum of the neuronal firing by the receiving neurons, generalisation and graceful degradation. These invariant representations are ideally suited to provide the inputs to brain regions such as the orbitofrontal cortex and amygdala that learn the reinforcement associations of an individual's face, for then the learning, and the appropriate social and emotional responses, generalise to other views of the same face. A theory is described of how such invariant representations may be produced in a hierarchically organised set of visual cortical areas with convergent connectivity. The theory proposes that neurons in these visual areas use a modified Hebb synaptic modification rule with a short-term memory trace to capture whatever can be captured at each stage that is invariant about objects as the objects change in retinal view, position, size and rotation. Another population of neurons in the cortex in the superior temporal sulcus encodes other aspects of faces such as face expression, eye gaze, face view and whether the head is moving. These neurons thus provide important additional inputs to parts of the brain such as the orbitofrontal cortex and amygdala that are involved in social communication and emotional behaviour. Outputs of these systems reach the amygdala, in which face-selective neurons are found, and also the orbitofrontal cortex, in which some neurons are tuned to face identity and others to face expression. In humans, activation of the orbitofrontal cortex is found when a change of face expression acts as a social signal that behaviour should change; and damage to the orbitofrontal cortex can impair face and voice expression identification, and also the reversal of emotional behaviour that normally occurs when reinforcers are reversed.
Keywords: Animals, Computer Simulation, Facial Expression, Frontal Lobe/physiology, Gesicht und assoziierte Zuschreibungen, Gesichtserkennung, Gesichtszüge, Gestik/Mimik, Haplorhini, hierarchy, Humans, Mensch oder Tier, Neurowissenschaften, Social Perception, Temporal Lobe/physiology, Tier und Mensch 2004
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(2004): Models of social networks based on social distance attachment. In: Physical review. E, Statistical, nonlinear, and soft matter physics 70 (5 Pt 2). DOI: 10.1103/PhysRevE.70.056122
DOI: http://www.ncbi.nlm.nih.gov/pubmed/15600707 Abstract: We propose a class of models of social network formation based on a mathematical abstraction of the concept of social distance. Social distance attachment is represented by the tendency of peers to establish acquaintances via a decreasing function of the relative distance in a representative social space. We derive analytical results (corroborated by extensive numerical simulations), showing that the model reproduces the main statistical characteristics of real social networks: large clustering coefficient, positive degree correlations, and the emergence of a hierarchy of communities. The model is confronted with the social network formed by people that shares confidential information using the Pretty Good Privacy (PGP) encryption algorithm, the so-called web of trust of PGP.
Keywords: Algorithms, Computer Simulation, degree of acquaintance, Disziplin, Favoriten, Gruppenverhalten / Joint Action, Hierarchy, Social, Interpersonal Relations, Modelle/Theorien, Models, Biological, Netzwerktheorien, Population Dynamics, Residence Characteristics, Social Behavior, Social Change, Social Distance, social networks based on social distance, Social Support, Soziale Angemessenheit, Soziale Distanz, Soziologie, SV 2002
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(2002): Collision warning timing, driver distraction, and driver response to imminent rear-end collisions in a high-fidelity driving simulator. In: Human factors 44 (2), S. 314-334. DOI: 10.1518/0018720024497844
DOI: http://www.ncbi.nlm.nih.gov/pubmed/12452276 Abstract: Rear-end collisions account for almost 30% of automotive crashes. Rear-end collision avoidance systems (RECASs) may offer a promising approach to help drivers avoid these crashes. Two experiments performed using a high-fidelity motion-based driving simulator examined driver responses to evaluate the efficacy of a RECAS. The first experiment showed that early warnings helped distracted drivers react more quickly--and thereby avoid more collisions--than did late warnings or no warnings. Compared with the no-warning condition, an early RECAS warning reduced the number of collisions by 80.7%. Assuming collision severity is proportional to kinetic energy, the early warning reduced collision severity by 96.5%. In contrast, the late warning reduced collisions by 50.0% and the corresponding severity by 87.5%. The second experiment showed that RECAS benefits even undistracted drivers. Analysis of the braking process showed that warnings provide a potential safety benefit by reducing the time required for drivers to release the accelerator. Warnings do not, however, speed application of the brake, increase maximum deceleration, or affect mean deceleration. These results provide the basis for a computational model of driver performance that was used to extrapolate the findings and identify the most promising parameter settings. Potential applications of these results include methods for evaluating collision warning systems, algorithm design guidance, and driver performance model input.
1998
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(1998): Evolution of indirect reciprocity by image scoring. In: Nature 393 (6685), S. 573-577. DOI: 10.1038/31225
DOI: http://www.ncbi.nlm.nih.gov/pubmed/9634232 Abstract: Darwinian evolution has to provide an explanation for cooperative behaviour. Theories of cooperation are based on kin selection (dependent on genetic relatedness), group selection and reciprocal altruism. The idea of reciprocal altruism usually involves direct reciprocity: repeated encounters between the same individuals allow for the return of an altruistic act by the recipient. Here we present a new theoretical framework, which is based on indirect reciprocity and does not require the same two individuals ever to meet again. Individual selection can nevertheless favour cooperative strategies directed towards recipients that have helped others in the past. Cooperation pays because it confers the image of a valuable community member to the cooperating individual. We present computer simulations and analytic models that specify the conditions required for evolutionary stability of indirect reciprocity. We show that the probability of knowing the 'image' of the recipient must exceed the cost-to-benefit ratio of the altruistic act. We propose that the emergence of indirect reciprocity was a decisive step for the evolution of human societies.
Keywords: Altruism, Biological Evolution, Computer Simulation, Cooperative Behavior, Evolutionsbiologie, Good manners, Helping Behavior, Humans, Indirect reciprocity model, Indirekte Reziprozität, Interaktion, Kooperation, Mutation, Reziprozität, Selection, Genetic, Soziale Angemessenheit, Spieltheorie 1977
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(1977): Resilience, Hypotheticality and Computers. Designing Social Systems under Uncertainty. In: Proceedings of the American Philosophical Society (121/5), S. 346-349
Abstract: OVER TWO THOUSAND years ago, Archimedes invented some formidable, for his time, machines. And, in a moment of forgivable boastfulness, he isreported to have said: "Give me where to stand, and I shall move the earth." Since his day, man- kind has generated the energy to move the earth and has set about transforming it, often to our satisfaction, not infrequently to our regret. And we know where is Archimedes' place to stand: technology. About twenty-five years ago, computing machines made their appearance. A computing machine is a means for multiplying mankind's capacity to generate, manage, and apply information, just as Archimedes' machines were force- multiplying devices. Where energy machines give us the power to alter natural systems, to fashion the physical world to a state we believe we shall like better, information machines may give us expanded analytical power to foresee the conse- quences of technological choice. However, much of the computer simulation of social and physical systems falls far short of demonstrating the reality of this hope. Economic models do not yet provide unambiguous direction to economic planners. The use by the Club of Rome's Limits to Growth project, of what Gerald Piel calls the "awesome authority of the computer" to forecast a dismal fate for mankind, undoubtedly helped catch the public's attention. But whether it advanced the reputation of computer simulation of complex social processes is more debatable.
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