This work was presented at HAIDM 2015. The 2015 workshop on Human-Agent Interaction Design and Models was co-organised by SmartSociety.

Abstract: We study simulation models of spreading on peer-to-peer communication networks where any peer (or agent) can be the source of information, be it sensory recognition or contextual knowledge. In such a situation the value or quality of information is of key relevance. Questions of trust, provenance and the problem of the interaction pattern arise and are approached by three different algorithms in our paper: (i) “quantitative democracy”, where knowledge is averaged on a meeting (ii) “experience takes all”, where the more experienced (the teacher) overwrites all prior knowledge of the less experienced (the “student”), and (iii) “transitive experience” where not only information but also experience is handed over. We compare these different regimes and identify their tradeoffs.

Keywords: Trust, provenance, self-organization, emergence, collaborative information processing.

Citation: George Kampis and Paul Lukowicz. Collaborative Activity Recognition.

Download: http://bit.ly/1SQJhad

This work was presented at HAIDM 2015. The 2015 workshop on Human-Agent Interaction Design and Models was co-organised by SmartSociety.

Abstract: Trust is an important factor in any relationship and within teamwork is no exception. Teammates need to trust each other to achieve common tasks effectively and efficiently. Teamwork that combines both a human and an Intelligent Virtual Agent (IVA) has drawn much interest; nevertheless, the handling of trust between humans and IVAs is unclear. In this paper, we seek to understand how people trust an IVA teammate. The current study considers two facets of trust: personality and cognition. Our experimental study with 55 participants, involving a collaborative human-IVA task, sought to determine whether human trust in an IVA teammate is affected by the IVA’s personality and whether that differs when the IVA’s personality matches the human’s personality. Furthermore, we sought to understand the relative importance of personality-based versus cognitive-based facets (e.g. the information offered by the IVA) on human trust in the IVA and the resultant effect of human trust on team performance. Results indicated that cognitive-based facets played a more dominant role in establishing trust than personality-based facets. Additionally, the results showed that human trust in the IVA had a significantly positive influence on human-IVA team performance.

Keywords: Intelligent Virtual Agent, Human-Agent Teamwork, Multimodal Communication, Trust, Personality, FFM, Team Performance.

Citation: Nader Hanna and Deborah Richards. In the Agent we Trust! The Role of Personality and Cognition in Human Trust in Virtual Agents.

Download: http://bit.ly/23I9B1H

This work was presented at HAIDM 2015. The 2015 workshop on Human-Agent Interaction Design and Models was co-organised by SmartSociety.

Abstract: With the improvement in agent technology and agent capabilities we foresee increasing use of agents in social contexts and, in particular, in human-agent team applications. To be effective in such team contexts, agents need to understand and adapt to the expectation of human team members. This paper presents our study on how behavioral strategies of agents affect the humans’ trust in those agents and the concomitant performance expectations that follow in virtual team environments. We have developed a virtual teamwork problem that involves repeated interaction between a human and several agent types over multiple episodes. The domain involves transcribing spoken words, and was chosen so that no specialized knowledge beyond language expertise is required of the human participants. The problem requires humans and agents to independently choose subset of tasks to complete without consulting with the partner and utility obtained is a function of the payment for task, if completed, minus its efforts. We implemented several agents types, which vary in how much of the teamwork they perform over different interactions in an episode. Experiments were conducted with subjects recruited from the MTurk. We collected both teamwork performance data as well as surveys to gauge participants’ trust in their agent partners. We trained a regression model on collected game data to identify distinct behavioral traits. By integrating the prediction model of player’s task choice, a learning agent is constructed and shown to significantly improve both social welfare, by reducing redundant work without sacrificing task completion rate, as well as agent and human utilities.

Keywords: Human-agent interaction, teamwork, trust, adaptation.

Citation: Feyza Hafizoglu and Sandip Sen. Evaluating Trust Levels in Human-agent Teamwork in Virtual Environments.

Download: http://bit.ly/1S8ceCA

Abstract: With the advance of research in human computation, applications and software systems are increasingly being designed to include the human aspect of computation. We work with Social Compute Units (SCUs) that are computational constructs with people as their core resources. They are collaborative units, and have a cloud-like behavior in the sense that they may be elastically adapted at runtime. Systems that utilize the concept of SCUs bring challenges that are associated with the highly dynamic and unpredictable human-centric behavior. Thus, trust in the human based services that execute tasks is of paramount importance. While there is related work on social trust in the social networking and crowdsourcing areas, trust in highly coordinated team-based systems such as SCUs remains as a significant challenge. Thus, in this paper we provide a trust model that considers merging social trust with performance based trust of human based services into an integrated trust model. We illustrate the models’ application in concrete strategies, such as for elastic management of SCUs and incentives for SCU members.

Citation: Mirela Riveni, Hong-Linh Truong, Schahram Dustdar, “Trust-aware Elastic Social Compute Units”, The 14th IEEE International Conference on Trust, Security and Privacy in Computing and Communications (IEEE TrustCom-15), Helsinki, Finland, 20-22 August 2015.

Download: http://bit.ly/1SnmHw4