Results 1 - 10
of
46
BiLAT: A game-based environment for practicing negotiation in a cultural context
- International Journal of Artificial Intelligence in Education
, 2009
"... Abstract. Negotiation skills are essential in everyday life, whether in a professional or personal context. Negotiation enables two parties to address misunderstandings and avoid conflicts through an exchange that depends as much on the interpersonal skills of the negotiators as the tactics employed ..."
Abstract
-
Cited by 41 (14 self)
- Add to MetaCart
Abstract. Negotiation skills are essential in everyday life, whether in a professional or personal context. Negotiation enables two parties to address misunderstandings and avoid conflicts through an exchange that depends as much on the interpersonal skills of the negotiators as the tactics employed. Acquiring these skills requires not only sound conceptual knowledge but also practice and mentoring. This paper describes the BiLAT game-based simulation and tutoring system developed to provide students, initially United States Army soldiers, with an environment to practice preparing for and conducting bilateral negotiations. We describe the models that were created to implement BiLAT, with a particular focus on the challenge of designing for and tutoring in the ill-defined domain of negotiation. An initial assessment of the training effectiveness of the system indicates significant situation-judgment gains by novices.
Too close for comfort? Adapting to the user’s cultural background
- IN: WORKSHOP ON HUMAN-CENTERED MULTIMEDIA, ACM MULTIMEDIA
, 2007
"... The cultural context of the user is a largely neglected aspect of human centered computing. This is because culture is a very fuzzy concept and even with a computational model of culture it remains difficult to derive the necessary information to recognize the user’s cultural background. Such inform ..."
Abstract
-
Cited by 10 (7 self)
- Add to MetaCart
(Show Context)
The cultural context of the user is a largely neglected aspect of human centered computing. This is because culture is a very fuzzy concept and even with a computational model of culture it remains difficult to derive the necessary information to recognize the user’s cultural background. Such information is only indirectly available and has to be derived from the observable multimodal behavior of the user. We propose the usage of a dimensional model of culture that allows applying computational methods to derive a user’s cultural background and to adjust the system’s behavior accordingly. To this end, a Bayesian network is applied to allow for the necessary inferences despite the fact that the given knowledge about the user’s behavior is incomplete and unreliable.
AffectButton: a method for reliable and valid affective self-report
"... In this article we report on a new digital interactive self-report method for the measurement of human affect. The AffectButton (Broekens & Brinkman, 2009) is a button that enables users to provide affective feedback in terms of values on the well-known three affective dimensions of Pleasure (Va ..."
Abstract
-
Cited by 9 (2 self)
- Add to MetaCart
In this article we report on a new digital interactive self-report method for the measurement of human affect. The AffectButton (Broekens & Brinkman, 2009) is a button that enables users to provide affective feedback in terms of values on the well-known three affective dimensions of Pleasure (Valence), Arousal and Dominance. The AffectButton is an interface component that functions and looks like a medium-sized button. The button presents one dynamically changing iconic facial expression that changes based on the coordinates of the user’s pointer in the button. To give affective feedback the user selects the most appropriate expression by clicking the button, effectively enabling 1-click affective self-report on 3 affective dimensions. Here we analyze 5 previously published studies, and 3 novel large-scale studies (n=325, n=202, n=128). Our results show the reliability, validity, and usability of the button for acquiring three types of affective feedback in various domains. The tested domains are holiday preferences, real-time music annotation, emotion words, and textual situation descriptions (ANET). The types of affective feedback tested are preferences, affect attribution to the previously mentioned stimuli, and self-reported mood. All of the subjects tested were Dutch and aged between 15 and 56 years. We end this article with a discussion of the limitations of the AffectButton and of its relevance to areas including recommender systems, preference elicitation, social computing, online surveys, coaching and tutoring, experimental psychology and psychometrics, content annotation, and game consoles. 1
Virtual Reality Negotiation Training Increases Negotiation Knowledge and Skill
"... Abstract. In this paper we test the hypothesis that Virtual Reality (VR) negotiation training positively influences negotiation skill and knowledge. We discuss the design of the VR training. Then, we present the results of a between subject experiment (n=42) with three experimental conditions (contr ..."
Abstract
-
Cited by 9 (4 self)
- Add to MetaCart
(Show Context)
Abstract. In this paper we test the hypothesis that Virtual Reality (VR) negotiation training positively influences negotiation skill and knowledge. We discuss the design of the VR training. Then, we present the results of a between subject experiment (n=42) with three experimental conditions (control, training once, repeated training) investigating learning effects on subjects ’ negotiation skill and knowledge. In our case negotiation skill consists of negotiation outcome (final bid utility) and conversation skill (exploratory conversational choices in VR scenario), and negotiation knowledge is the subjects ’ quality of reflection upon filmed behavior of two negotiating actors. Our results confirm the hypothesis. We found significant effects of training on conversation skill and negotiation knowledge. We found a marginally significant effect of training on negotation outcome. As the effect of training on negotiation outcome was marginally significant and only present when controlling for overshadowing effects of the act of reflecting, we postulate that other learning approaches (e.g., instruction) are needed for trainees to use the information gained during the joint exploration phase of a negotiation for the construction of a bid. Our results are particularly important given the sparse availability of experimental studies that show learning effects of VR negotiation training, and gives additional support to those studies that do report possitive effects such as with the BiLAT system. 1
Culture-specific first meeting encounters between virtual agents
- In: Intelligent Virtual Agents 2008
, 2008
"... Abstract. We present our concept of integrating culture as a computational parameter for modeling multimodal interactions with virtual agents. As culture is a social rather than a psychological notion, its influence is evident in interactions, where cultural patterns of behavior and interpretations ..."
Abstract
-
Cited by 9 (5 self)
- Add to MetaCart
(Show Context)
Abstract. We present our concept of integrating culture as a computational parameter for modeling multimodal interactions with virtual agents. As culture is a social rather than a psychological notion, its influence is evident in interactions, where cultural patterns of behavior and interpretations mismatch. Nevertheless, taking culture seriously its influence penetrates most layers of agent behavior planning and generation. In this article we concentrate on a first meeting scenario, present our model of an interactive agent system and identify, where cultural parameters play a role. To assess the viability of our approach, we outline an evaluation study that is set up at the moment. 1
Metacognition and the development of intercultural competence
- In Proceedings of the Workshop on Metacognition and Self-Regulated Learning in Intelligent Tutoring Systems at the 13 th International Conference on Artificial Intelligence in Education (AIED
, 2007
"... ..."
(Show Context)
Toward Rapid Development of Multiparty Virtual Human Negotiation Scenarios
- Proc. 15th Workshop Semantics and Pragmatics of Dialogue (SemDial
"... This paper reports on an ongoing effort to enable the rapid development of multi-party virtual human negotiation scenarios. We present a case study in which a new scenario supporting negotiation between two human role players and two virtual humans was developed over a period of 12 weeks. We discuss ..."
Abstract
-
Cited by 5 (4 self)
- Add to MetaCart
This paper reports on an ongoing effort to enable the rapid development of multi-party virtual human negotiation scenarios. We present a case study in which a new scenario supporting negotiation between two human role players and two virtual humans was developed over a period of 12 weeks. We discuss the methodology and development process that were employed, from storyline design through role play and iterative development of the virtual humans ’ semantic and task representations and natural language processing capabilities. We analyze the effort, expertise, and time required for each development step, and discuss opportunities to further streamline the development process. 1
Dynamic Facial Expression of Emotion Made Easy
, 2012
"... Abstract. Facial emotion expression for virtual characters is used in a wide variety of areas. Often, the primary reason to use emotion expression is not to study emotion expression generation per se, but to use emotion expression in an application or research project. What is then needed is an easy ..."
Abstract
-
Cited by 5 (4 self)
- Add to MetaCart
Abstract. Facial emotion expression for virtual characters is used in a wide variety of areas. Often, the primary reason to use emotion expression is not to study emotion expression generation per se, but to use emotion expression in an application or research project. What is then needed is an easy to use and flexible, but also validated mechanism to do so. In this report we present such a mechanism. It enables developers to build virtual characters with dynamic affective facial expressions. The mechanism is based on Facial Action Coding. It is easy to implement, and code is available for download. To show the validity of the expressions generated with the mechanism we tested the recognition accuracy for 6 basic emotions (joy, anger, sadness, surprise, disgust, fear) and 4 blend emotions (enthusiastic, furious, frustrated, and evil). Additionally we investigated the effect of VC distance (z-coordinate), the effect of the VC’s face morphology (male vs. female), the effect of a lateral versus a frontal presentation of the expression, and the effect of intensity of the expression. Participants (n=19, Western and Asian subjects) rated the intensity of each expression for each condition (within subject setup) in a non forced choice manner. All of the basic emotions were uniquely perceived as such. Further, the blends and confusion details of basic emotions are compatible with findings in psychology.
Explaining simulations through self explaining agents.
- Journal of Artificial Societies and Social Simulation,
, 2010
"... Abstract Several strategies are used to explain emergent interaction patterns in agent-based simulations. A distinction can be made between simulations in which the agents just behave in a reactive way, and simulations involving agents with also pro-active (goal-directed) behavior. Pro-active behav ..."
Abstract
-
Cited by 5 (2 self)
- Add to MetaCart
Abstract Several strategies are used to explain emergent interaction patterns in agent-based simulations. A distinction can be made between simulations in which the agents just behave in a reactive way, and simulations involving agents with also pro-active (goal-directed) behavior. Pro-active behavior is more variable and harder to predict than reactive behavior, and therefore it might be harder to explain. However, the approach presented in this paper tries to make advantage of the agents' pro-activeness by using it to explain their behavior. The aggregation of the agents' explanations form a basis for explaining the simulation as a whole. In this paper, an agent model that is able to generate (pro-active) behavior and explanations about that behavior is introduced, and the implementation of the model is discussed. Examples show how the link between behavior generation and explanation in the model can contribute to the explanation of a simulation.