The present study describes the process employed to identify a suitable intelligent virtual agent (IVA) for the AMPER App supporting reminiscence therapy for those living with dementia through the use of a facilitating agent. This included three distinct phases: 1) co-creation with project stakeholders and identification of a set of desirable IVA traits; 2) a blind internal team rating process to select a subset from available IVAs; 3) a character survey with healthy older adults to select a final 4 IVAs (2 male, 2 female). We analyse the results, assess inter-subject agreement, and suggest guidelines for IVA selection.

We present a demonstration of the AMPER system: an Android application that guides individuals with Alzheimer’s disease and their carers through reminiscence therapy with the use of a virtual agent. The application supports a novel method of reminiscence story selection, using material metadata, user data, and a spreading activation algorithm. This aims to present relevant material to the user, in an order that attempts to mimic a human autobiographical memory.

We focus on affective architecture issues relating to the generation of expressive facial behaviour, critique approaches that treat expressive behaviour as only a mirror of internal state rather than as also a social signal and discuss the advantages of combining the two approaches. Using the FAtiMA architecture, we analyse the requirements for generating expressive behavior as social signals at both reactive and cognitive levels. We discuss how facial expressions can be generated in a dynamic fashion. We propose generic architectural mechanisms to meet these requirements based on an explicit mind-body loop and Theory of Mind (ToM) processing. A illustrative scenario is given.

Emotion expressions and communication involve involuntary and voluntary processes that may not always operate consistently. Expressive behaviour involving physiological changes may carry information about hidden aspects of emotional experience important for accurate emotion recognition and social cognition. In this paper, we describe a principled approach to simulating Virtual Human physiological facial features related to the autonomic nervous system (ANS). Our approach is based on typical synergies within the two branches of the ANS. It covers both parasympathetic tone and sympathetic tone, and their impact on skin tone, pupil diameter and sweat. We also present the triggering of tears. We discuss the implementation of the approach as part of a 3D toolkit. This work is aimed at supporting the development of affective features for realtime intelligent artificial agents, and the study of the perception of mixed emotion and emotion regulation. We demonstrate how varying ANS parameters impacts facial behaviour, contrasting emotionally consistent vs inconsistent musculoskeletal and ANS-related features.

Social robots are being developed as a form of social skills training for individual's with an autism spectrum condition (ASC). Effective training will therefore require the social signals produced by a robot to be contingent with people's knowledge and expectations of social cognition and behaviour. Designing recognisable facial expressions is an important part of this challenge; ensuring interactions are more believable and motivating. This design process requires - amongst other factors - consideration of how culture and native language affects social signal processing. In this experiment participants offered a full-bodied robot (named 'Alyx') food items to which Alyx reacted autonomously, producing either an approving or disapproving expression. Participant's responded to these expressions (i.e. the robots social signals) by indicating whether Alyx liked or disliked the food. Task performance was examined both quantitatively (response time and accuracy) and qualitatively (participant's reactionary expressions). The results revealed significant cultural differences, as non-native English speakers were less accurate at interpreting expressions, but also a similar response trend between these groups. Qualitative analysis supported the notion that Alyx's expressions were not universally understood. These findings are discussed in the context of social skills training.

This paper outlines a demonstration of the work carried out in the SoCoRo project investigating how far a neuro-typical population recognises facial expressions on a non-naturalistic robot face that are designed to show approval and disapproval. RFID-tagged objects are presented to an Emys robot head (called Alyx) and Alyx reacts to each with a facial expression. Participants are asked to put the object in a box marked 'Like' or 'Dislike'. This study is being extended to include assessment of participants' Autism Quotient using a validated questionnaire as a step towards using a robot to help train high-functioning adults with an Autism Spectrum Disorder in social signal recognition.

We present a study investigating the expressiveness of two different types of robots in a tutoring task. The robots used were i) the EMYS robot, with facial expression capabilities, and ii) the NAO robot, without facial expressions but able to perform expressive gestures. Preliminary results show that the NAO robot was perceived to be more friendly, pleasant and empathic than the EMYS robot as a tutor in a learning environment.

In this video submission, we describe a scenario developed in the EMOTE project. The overall goal of the EMOTE project is to develop an empathic robot tutor for 11-13 year old school students in an educational setting. The pedagogical domain here is to assist students in learning and testing their map-reading skills typically learned as part of the geography curriculum in schools. We show this scenario with a NAO robot interacting with the students whilst performing map-reading tasks on a touch-screen device in this video.

This work addresses the challenge of creating virtual agents that are able to portray culturally appropriate behavior when interacting with other agents or humans. Because culture influences how people perceive their social reality it is important to have agent models that explicitly consider social elements, such as existing relational factors. We addressed this necessity by integrating culture into a novel model for simulating human social behavior. With this model, we operationalized a particular dimension of culture—individualism versus collectivism—within the context of an interactive narrative scenario that is part of an agent-based tool for intercultural training. Using this scenario we conducted a cross-cultural study in which participants from a collectivistic country (Portugal) were compared with participants from an individualistic country (the Netherlands) in the way they perceived and interacted with agents whose behavior was either individualistic or collectivistic, according to the configuration of the proposed model. In the obtained results, Portuguese subjects rated the collectivistic agents more positively than the Dutch but both countries had a similarly positive opinion about the individualistic agents. This experiment sheds new light on how people from different countries differ when assessing the social appropriateness of virtual agents, while also raising new research questions on this matter.

The aim of this paper is to give a short overview on how facial expressions enhance interaction with elderly people. Two studies were done. The first one was an online questionnaire that gave information on what type of expressions were more appropriate and the second one was an experiment in which participants met the robot. This study's results suggested a correlation between facial expressions and interaction enhancement. Participants preferred a certain motor speed according to the facial expression presented which shows that speed has an influence on understanding expressions and beyond this, emotions. In the end, this paper presents some ways of enhancing interaction with the robot.

In this paper we try to highlight the need for social intelligence during the recharge activity of mobile robots and report a study performed to investigate people's attitude towards recharge behaviour of an office robot.

There are several challenges in applying conversational social robots to Technology Enhanced Learning and Serious Gaming. In this paper, we focus in particular on the dialogue management issues in building an empathic robotic tutor that plays a multi-person serious game with students to help them learn and understand the underlying educational concepts.

There has been some studies in applying robots to education and recent research on socially intelligent robots show robots as partners that collaborate with people. On the other hand, serious games and interaction technologies have also proved to be important pedagogical tools, enhancing collaboration and interest in the learning process. This paper relates to the collaborative scenario in EMOTE EU FP7 project and its main goal is to develop and present the dialogue dimensions for a robotic tutor in a collaborative learning scenario grounded in human studies. Overall, seven dialogue dimensions between the teacher and students interaction were identified from data collected over 10 sessions of a collaborative serious game. Preliminary results regarding the teachers perspective of the students interaction suggest that student collaboration led to learning during the game. Besides, students seem to have learned a number of concepts as they played the game. We also present the protocol that was followed for the purposes of future data collection in human-human and human-robot interaction in similar scenarios.

In this paper, a robot that is using politeness to overcome its incapability to serve is presented. The mobile robot “Alex” is interacting with human office colleagues in their environment and delivers messages, phone calls, and companionship. The robot's battery capacity is not sufficient to survive a full working day. Thus, the robot needs to recharge during the day. By doing so it is unavailable for tasks that involve movement. The study presented in this paper supports the idea that an incapability of fullfiling an appointed task can be overcome by politeness and showing appropriate behaviour. The results, reveal that, even the simple adjustment of spoken utterances towards a more polite phrasing can change the human's perception of the robot companion. This change in the perception can be made visible by analysing the human's behaviour towards the robot.

This paper considers the generation of emergent structure, as a source of creativity. It discusses emergent narrative in which narrative structure is generated dynamically by interaction between synthetic characters, as a cognitive model of bottom-up character-based authoring. It considers the affectively-driven agent architecture FAtiMA, and the use of a story-facilitator agent and character-based double-appraisal mechanism as means of dealing with narrative-level constraints.

This paper investigates user perceptions of continuous identity as agents migrate between different embodiments. It reports an experiment seeking to establish whether migrating or not migrating the interaction memory of the agent would affect the user's perception of consistent agent identity over different embodiments. The experiment involved a treasure hunt in which a virtual agent migrated from a screen to a mobile phone in order to accompany a user while they searched for clues. A total of 45 subjects took part in three different conditions with 15 subjects in each. The outcome showed that the presence of memory affected the competence users ascribed to the virtual agent. However it had no significant effect on a strong perception of consistent identity across multiple embodiments.

Autonomous robots acting as companions or assistants in real social environments should be able to sustain and operate over an extended period of time. Generally, autonomous mobile robots draw power from batteries to operate various sensors, actuators and perform tasks. Batteries have a limited power life and take a long time to recharge via a power source, which may impede human-robot interaction and task performance. Thus, it is important for social robots to manage their energy, this paper discusses an approach to manage power resources on mobile robot with regard to social aspects for creating life-like autonomous social robots.

In this paper, we present an approach to monitor human activities such as entry, exit and break times of people in a workplace environment. The companion robot then learns the users' presence patterns over a period of time through memory generalisation and plans a suitable time for re charging itself causing less hindrance to human-robot interaction.

This paper gives a brief overview of the challenges for multi-model perception and generation applied to robot companions located in human social environments. It reviews the current position in both perception and generation and the immediate technical challenges and goes on to consider the extra issues raised by embodiment and social context. Finally, it briefly discusses the impact of systems that must function continually over months rather than just for a few hours.

This paper presents FearNot!, an innovative anti-bullying intervention for 8-12 year old children, illustrating the potential of Virtual Learning Environments in providing supportive secure experiential learning for challenging social situations. The innovative technological approach taken to FearNot! is briefly described, along with an overview of the evaluation approach used to assess FearNot! with over 800 children in the UK and Germany. The demo of FearNot! provides participants with the opportunity to experience leading edge technology adopted for a classroom intervention.

This work proposes an initial memory model for a long-term artificial companion, which migrates among virtual and robot platforms based on the context of interactions with the human user. This memory model enables the companion to remember events that are relevant or significant to itself or to the user. For other events which are either ethically sensitive or with a lower long-term value, the memory model supports forgetting through the processes of generalisation and memory restructuring. The proposed memory model draws inspiration from the human short-term and long-term memories. The short-term memory will support companions in focusing on the stimuli that are relevant to their current active goals within the environment. The long-term memory will contain episodic events that are chronologically sequenced and derived from the companion's interaction history both with the environment and the user. There are two key questions that we try to address in this work: 1) What information should the companion remember in order to generate appropriate behaviours and thus smooth the interaction with the user? And, 2) What are the relevant aspects to take into consideration during the design of memory for a companion that can have different types of virtual and physical bodies? Finally, we show an implementation plan of the memory model, focusing on issues of information grounding, activation and sensing based on specific hardware platforms.

The MY virtual graffiti (MYVG) system is an artistic medium that uses two sensor gloves, a six degree of freedom hand-held controller (Space Orb 360/spl deg/), a tracking system and dummy spray can nozzle strokes to create graffiti in a fully immersive CAVE environment. It redefines the traditional communication and art form of graffiti using virtual reality technology. Realistic paint splat is simulated directly on 3D objects in the virtual world. The paper describes the interaction devices, spray paint simulation algorithm, 3D colour and nozzle picker and the intuitive user interface for creating and storing graffiti. Users' evaluation result along with some sample graffiti are presented.

This paper describes an on-going study which applies the concept of transitivity to news discourse for text processing tasks. The complex notion of transitivity is defined and the relatioship between transitivity and information foregrounding is explained. A sample corpus of news articles has been coded for transitivity. The corpus is being used in two text processing experiments.