Werewolves, cheats, and cultural sensitivity

This paper discusses the design and evaluation of the system MIXER (Moderating Interactions for Cross-Cultural Empathic Relationships), which applies a novel approach to the education of children in cultural sensitivity. MIXER incorporates intelligent affective and interactive characters, including a model of a Theory of Mind mechanism, in a simulated virtual world. We discuss the relevant pedagogical approaches, related work, the underlying mind model used for MIXER agents as well as its innovative interaction interface utilising a tablet computer and a pictorial interaction language. We then consider the evaluation of the system, whether this shows it met its pedagogical objectives, and what can be learned from our results.</p

Small talk is more than chit-chat: Exploiting structures of casual conversations for a virtual agent

Mattar N, Wachsmuth I. Small talk is more than chit-chat: Exploiting structures of casual conversations for a virtual agent. In: Glimm B, Krüger A, eds. KI 2012: Advances in Artificial Intelligence. Lecture Notes in Computer Science. Vol 7526. Berlin, Heidelberg: Springer Berlin Heidelberg; 2012: 119-130

Combining heterogeneous inputs for the development of adaptive and multimodal interaction systems

In this paper we present a novel framework for the integration of visual sensor networks and speech-based interfaces. Our proposal follows the standard reference architecture in fusion systems (JDL), and combines different techniques related to Artificial Intelligence, Natural Language Processing and User Modeling to provide an enhanced interaction with their users. Firstly, the framework integrates a Cooperative Surveillance Multi-Agent System (CS-MAS), which includes several types of autonomous agents working in a coalition to track and make inferences on the positions of the targets. Secondly, enhanced conversational agents facilitate human-computer interaction by means of speech interaction. Thirdly, a statistical methodology allows modeling the user conversational behavior, which is learned from an initial corpus and improved with the knowledge acquired from the successive interactions. A technique is proposed to facilitate the multimodal fusion of these information sources and consider the result for the decision of the next system action.This work was supported in part by Projects MEyC TEC2012-37832-C02-01, CICYT TEC2011-28626-C02-02, CAM CONTEXTS S2009/TIC-1485Publicad

Planning Smalltalk Behavior with Cultural Influences for Multiagent Systems

International audienceThere are several factors that inuence communicative behavior, such as gen- der, personality or culture. As virtual agents interact in a more and more human-like manner, their behavior should be dependent on social factors as well. Culture is a phenomenon that a_ects one's behavior without one realiz- ing it. Behavior is thus sometimes perceived as inappropriate because there is no awareness of the cultural gap. Thus, we think cultural background should also inuence the communication behavior of virtual agents. Behav- ioral di_erences are sometimes easy to recognize by humans but still hard to describe formally, to enable integration into a system that automatically generates culture-speci_c behavior. In our work, we focus on culture-related di_erences in the domain of casual Small Talk. Our model of culture-related di_erences in Small Talk behavior is based on _ndings described in the lit- erature as well as on a video corpus that was recorded in Germany and Japan. In a validation study, we provide initial evidence that our simulation of culture-speci_c Small Talk with virtual agents is perceived di_erently by human observers. We thus implemented a system that automatically gener- ates culture-speci_c Small Talk dialogs for virtual agents

Talking topically to artificial dialog partners: Emulating humanlike topic awareness in a virtual agent

Breuing A, Wachsmuth I. Talking topically to artificial dialog partners: Emulating humanlike topic awareness in a virtual agent. In: Filipe J, Fred A, eds. Agents and Artificial Intelligence: 4th International Conference, ICAART 2012, Vilamoura, Portugal, February 6-8, 2012. Revised Selected Papers. Communications in Computer and Information Science. Vol 358. Berlin: Springer; 2013: 392-406.During dialog, humans are able to track ongoing topics, to detect topical shifts, to refer to topics via labels, and to decide on the appropriateness of potential dialog topics. As a result, they interactionally produce coherent sequences of spoken utterances assigning a thematic structure to the whole conversation. Accordingly, an artificial agent that is intended to engage in natural and sophisticated human-agent dialogs should be endowed with similar conversational abilities. This paper presents how to enable topically coherent conversations between humans and interactive systems by emulating humanlike topic awareness in the virtual agent Max. Therefore, we firstly realized automatic topic detection and tracking on the basis of contextual knowledge provided by Wikipedia and secondly adapted the agent’s conversational behavior by means of the gained topic information. As a result, we contribute to improve human-agent dialogs by enabling topical talk between human and artificial interlocutors. This paper is a revised and extended version of A. Breuing and I. Wachsmuth. Let’s talk topically with artificial agents! providing agents with humanlike topic awareness in everyday dialog situations. In Proceedings of the 4th International Conference on Agents and Artificial Intelligence (ICAART), pages 62–71, 2012

Designing a Chatbot Social Cue Configuration System

Social cues (e.g., gender, age) are important design features of chatbots. However, choosing a social cue design is challenging. Although much research has empirically investigated social cues, chatbot engineers have difficulties to access this knowledge. Descriptive knowledge is usually embedded in research articles and difficult to apply as prescriptive knowledge. To address this challenge, we propose a chatbot social cue configuration system that supports chatbot engineers to access descriptive knowledge in order to make justified social cue design decisions (i.e., grounded in empirical research). We derive two design principles that describe how to extract and transform descriptive knowledge into a prescriptive and machine-executable representation. In addition, we evaluate the prototypical instantiations in an exploratory focus group and at two practitioner symposia. Our research addresses a contemporary problem and contributes with a generalizable concept to support researchers as well as practitioners to leverage existing descriptive knowledge in the design of artifacts

Affect Detection from Text-Based Virtual Improvisation and Emotional Gesture Recognition

We have developed an intelligent agent to engage with users in virtual drama improvisation previously. The intelligent agent was able to perform sentence-level affect detection from user inputs with strong emotional indicators. However, we noticed that many inputs with weak or no affect indicators also contain emotional implication but were regarded as neutral expressions by the previous interpretation. In this paper, we employ latent semantic analysis to perform topic theme detection and identify target audiences for such inputs. We also discuss how such semantic interpretation of the dialog contexts is used to interpret affect more appropriately during virtual improvisation. Also, in order to build a reliable affect analyser, it is important to detect and combine weak affect indicators from other channels such as body language. Such emotional body language detection also provides a nonintrusive channel to detect users’ experience without interfering with the primary task. Thus, we also make initial exploration on affect detection from several universally accepted emotional gestures

To boldly go… : designing an agent-based intercultural training tool

People from all over the world must live and work together in today’s society. Such integration is not always a smooth process, and interactions with people from other cultures may lead to misunderstandings or even outright conflicts. In the last few years, researchers and practitioners have been working on creating digital tools that can be used to mediate these misunderstandings and conflicts. These tools typically involve interactions with so-called intelligent agents, i.e. virtual characters that are able to take decisions autonomously, that behave as if they are from another culture. The aim of these interactions is to make potential trainees experience how misunderstandings can shape interactions with and perceptions of people from other cultures. In this work, we take the first steps in the design of a digital culture-general training tool to help young adults deal with misunderstandings or conflicts due to differences in culture, through interactions with intelligent agents. We have posed the following design research questions and found the following answers: Which concepts are required to describe the design of a digital culture-general training tool involving agents that show culturally varying behaviour? The answer to this question can be found in the glossary, which presents the key concepts that have been used in this work to create agents that show culturally varying behaviour and to create scenarios that incorporate these agents to increase the intercultural competence of trainees. Can we use theories of culture to create scripted scenarios in which virtual characters behave appropriately for a given culture? To answer this question we designed scripted scenarios in which virtual characters show culturally varying behaviour based on a theory of culture. To ensure that the behaviours of these virtual characters were representative of real-life cultural differences, we conducted an evaluation with people from a wide range of cultures. The results show that the dimensions of culture can be used to generate culturally varying behaviour in agents, but that extensive (pre)testing is required to ensure that the underlying intention of the characters’ behaviour aligns with the users’ interpretation of that behaviour. Can we identify requirements for sociocultural agents that can help them to make sense of their social world? To answer this question we focused on describing important concepts of social interactions based on theories from sociology and psychology. These concepts are incorporated into a conceptual model for socio-cultural agents that can be used to describe their social world. The model differentiates between three levels of analysis: the interaction, the group, and the society. These levels range from being more specific, and thus more visible, to more abstract, and thus less visible, and help us to understand how each level affects interpretation and behaviour. Can we create intelligent agents that can vary their behaviour depending on the culture to be simulated? To answer this question we described the creation of intelligent agents that show culturally varying behaviour. We use an existing model to create believable social interactions, in which agents attribute, claim, and confer social importance in their interactions with other agents and users. Social importance is a way to measure the importance of a certain individual in the eyes of others. The strength of attribution, claims, and conferrals was varied using cultural modifiers. The generated behaviour of the agents was then evaluated to ensure that the intelligent agents showed behaviour representative of a given culture. The results suggest that it is possible to create intelligent agents that can act out appropriate culturally varying behaviour for a given culture. Can we create critical incidents, involving intelligent agents that show appropriate behaviour for given cultures, through which potential trainees become more sensitive to and knowledgeable about differences across cultures? To answer this question we focused on applying different methods of intercultural training in the design of a digital culture-general training tool. These methods were incorporated into critical incidents, in which users can interact with intelligent agents. To ensure that the critical incidents led to an attribution of perceived differences in behaviour to specific differences in culture and to (potential) trainees becoming less judgemental of inappropriate behaviours by people from different cultures, the tool was evaluated by two groups of students. The results suggest that it is possible to create agent-based critical incidents to make potential trainees more knowledgeable about differences across cultures. Contributions The findings to our design research questions represent a set of important contributions to the field. First, we have identified and structured important concepts to better understand the design and implementation of socio-cultural agents and the design of critical incidents that involve these agents for intercultural training. Second, we have described and used models that help to define the simulated world of the agents and help them to navigate through that world. Third, we have attempted to systematize the process of creating scenarios involving agents that show culturally varying behaviour through a set of guidelines that need to be met to ensure that the behaviour of socio-cultural characters is properly evaluated. Fourth, besides conceptual elements, we have also created practical implementations that can freely be used and modified by others. In our work, we have only taken the first steps in designing a digital culture-general training tool. Additional work on the generalization and validation of the critical incidents and the behaviours of the agents is still required; however, we believe that our results show our approach to be viable. We believe that future work will have to focus on three fields: understanding how trainees can be emotionally engaged in the scenarios, systematizing the process of using model-driven approaches to generate socio-cultural behaviour, and using the design outputs in different contexts and with different people from different cultures.</p