Alle Publikationen
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2016
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(2016): Selbstsicherheit und soziale Kompetenz. Das Trainingsprogramm TSK mit Basis- und Aufbauübungen. Stuttgart: Klett-Cotta (Leben lernen, Nr. 284)
Abstract: Vorgestellt wird ein für Therapeuten und Klienten als gemeinsamer Leitfaden konzipiertes Trainingsprogramm zum Erwerb sozialer Kompetenz. In 30 Übungsszenen führt das Training durch alle wichtigen sozialen Situationen in graduierter Vorgehensweise. Die beiliegende DVD vertieft den Lernprozess mit Filmsequenzen. Der erste Teil richtet sich speziell an die Teilnehmer des Trainings. Die theoretischen Grundlagen des Sozialen Kompetenztrainings werden im zweiten - an die Therapeuten gerichteten Teil - dargelegt. - Inhalt: (1) Selbstsicherheit und soziale Kompetenz - Was ist das eigentlich? (2) Die Entstehung (Genese) und Aufrechterhaltung von sozialen Ängsten und sozialen Phobien. (3) Durchführung des TSK - Basisübungen - Aufbauübungen. (4) Informationen für Therapeuten.
Keywords: Gesundheit, Interpersonal Interaction, Interpersonale Interaktion, Intervention Program, Psychotherapy & Psychotherapeutic Counseling, self-assurance & social competence, Interventionsprogramm, klinische Psychologie, social anxiety, social interaction, SOCIAL PHOBIA, patients & therapists, Psychotherapie und psychotherapeutische Beratung, social situation, Social Skills, Social Skills Training, Soziale Angst, Soziale Fertigkeiten, Soziale Interaktion, Soziale Phobie, Soziales Kompetenztraining, Sozialtherapie, training program, Training sozialer Fertigkeiten 2014
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(2014): Emotion attribution to a non-humanoid robot in different social situations. In: PLoS one 9 (12)
Abstract: In the last few years there was an increasing interest in building companion robots that interact in a socially acceptable way with humans. In order to interact in a meaningful way a robot has to convey intentionality and emotions of some sort in order to increase believability. We suggest that human-robot interaction should be considered as a specific form of inter-specific interaction and that human–animal interaction can provide a useful biological model for designing social robots. Dogs can provide a promising biological model since during the domestication process dogs were able to adapt to the human environment and to participate in complex social interactions. In this observational study we propose to design emotionally expressive behaviour of robots using the behaviour of dogs as inspiration and to test these dog-inspired robots with humans in inter-specific context. In two experiments (wizard-of-oz scenarios) we examined humans’ ability to recognize two basic and a secondary emotion expressed by a robot. In Experiment 1 we provided our companion robot with two kinds of emotional behaviour (’happiness’ and ’fear’), and studied whether people attribute the appropriate emotion to the robot, and interact with it accordingly. In Experiment 2 we investigated whether participants tend to attribute guilty behaviour to a robot in a relevant context by examining whether relying on the robot’s greeting behaviour human participants can detect if the robot transgressed a predetermined rule. Results of Experiment 1 showed that people readily attribute emotions to a social robot and interact with it in accordance with the expressed emotional behaviour. Results of Experiment 2 showed that people are able to recognize if the robot transgressed on the basis of its greeting behaviour. In summary, our findings showed that dog-inspired behaviour is a suitable medium for making people attribute emotional states to a non-humanoid robot. (PsycINFO Database Record (c) 2016 APA, all rights reserved)
Keywords: Adult, Age Factors, Angemessen(heit) (von Technik), Animals, Attitude, Attribution, Dogs, emotional behavior, Emotions, Female, Guilt, Humans, Interpersonal Relations, Male, non-humanoid robot, Questionnaires, Recognition (Psychology), Robotics, Sex Factors, social situation, Surveys, Young Adult 2008
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(2008) : Learning polite behavior with situation models: 3rd ACM/IEEE International Conference on Human-Robot Interaction (HRI): New York, NY, US: Association for Computing Machinery, S. 209-216
DOI: https://doi.org/10.1145/1349822.1349850 Abstract: In this paper, we describe experiments with methods for learning the appropriateness of behaviors based on a model of the current social situation. We first review different approaches for social robotics, and present a new approach based on situation modeling. We then review algorithms for social learning and propose three modifications to the classical Q-Learning algorithm. We describe five experiments with progressively complex algorithms for learning the appropriateness of behaviors. The first three experiments illustrate how social factors can be used to improve learning by controlling learning rate. In the fourth experiment we demonstrate that proper credit assignment improves the effectiveness of reinforcement learning for social interaction. In our fifth experiment we show that analogy can be used to accelerate learning rates in contexts composed of many situations.
Keywords: Angemessen(heit) (von Technik), Convergence, credit assignment, Humans, ieee xplore, Learning, learning (artificial intelligence), Learning by Analogy, machine learning, polite behavior, Q-Learning, Q-learning algorithm, Reinforcement learning, Robot sensing systems, Robots, situation modeling, social aspects of automation, Social factors, social interaction, social learning, Social robotic, social situation, standards 2006
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(2006) : Learning polite behavior with situation models: 3rd International Forum on Applied Wearable Computing 2006: Bremen, Germany: IEEE, S. 209-216
DOI: https://doi.org/10.1145/1349822.1349850 Abstract: In this paper, we describe experiments with methods for learning the appropriateness of behaviors based on a model of the current social situation. We first review different approaches for social robotics, and present a new approach based on situation modeling. We then review algorithms for social learning and propose three modifications to the classical Q-Learning algorithm. We describe five experiments with progressively complex algorithms for learning the appropriateness of behaviors. The first three experiments illustrate how social factors can be used to improve learning by controlling learning rate. In the fourth experiment we demonstrate that proper credit assignment improves the effectiveness of reinforcement learning for social interaction. In our fifth experiment we show that analogy can be used to accelerate learning rates in contexts composed of many situations.
Keywords: Convergence, credit assignment, Humans, ieee xplore, Künstliche Intelligenz, Learning, learning (artificial intelligence), Learning by Analogy, machine learning, polite behavior, Q-Learning, Q-learning algorithm, Reinforcement learning, Robot sensing systems, Robots, situation modeling, social aspects of automation, Social factors, social interaction, social learning, Social robotic, social situation, standards
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