Publications

@inproceedings{hartholt_creating_2023,

title = {Creating Virtual Worlds with the Virtual Human Toolkit and the Rapid Integration & Development Environment},

author = {Arno Hartholt and Sharon Mozgai},

url = {https://openaccess.cms-conferences.org/publications/book/978-1-958651-45-2/article/978-1-958651-45-2_41},

doi = {10.54941/ahfe1002856},

isbn = {978-1-958651-45-2},

year  = {2023},

date = {2023-07-01},

urldate = {2023-03-31},

booktitle = {Intelligent Human Systems Integration (IHSI 2023): Integrating People and Intelligent Systems},

volume = {69},

publisher = {AHFE Open Acces},

abstract = {The research and development of virtual humans, and the virtual worlds they inhabit, is inherently complex, requiring interdisciplinary approaches that combine social sciences, computer science, design, art, production, and domain expertise. Our previous work in managing this complexity has resulted in the release of the Virtual Human Toolkit (VHToolkit), aimed at lowering the burden of creating embodied conversational agents. In our current efforts, we are integrating the VHToolkit with the Rapid Integration & Development Environment (RIDE), a rapid prototyping modeling and simulation middleware platform that leverages real-time game engines. This integration results in the ability to mix and match commercial AI services from AWS, Azure, and Google, as well as leverage novel 3D geospatial terrain creation pipelines. Combined with dedicated authoring tools that have been developed through human-centered design processes, the platform enables researchers, developers, and domain experts to rapidly create digital worlds with virtual humans for both military and civilian contexts. Our approach is highly interdisciplinary, including academia, government, and industry collaborators. The demonstration shows a user interacting with an embodied conversational agent embedded within real-world captured and virtualized terrain. Further research and development features of the platform are shown, including scripted agent behaviors, networked team play, and machine learning interfaces.},

note = {ISSN: 27710718 

Issue: 69},

keywords = {DTIC, UARC, VHTL, Virtual Humans},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{mozgai_toward_2023,

title = {Toward a Scoping Review of Social Intelligence in Virtual Humans},

author = {Sharon Mozgai and Sarah Beland and Andrew Leeds and Jade G. Winn and Cari Kaurloto and Dirk Heylen and Arno Hartholt},

url = {https://ieeexplore.ieee.org/abstract/document/10042532},

doi = {10.1109/FG57933.2023.10042532},

year  = {2023},

date = {2023-01-01},

booktitle = {2023 IEEE 17th International Conference on Automatic Face and Gesture Recognition (FG)},

pages = {1–6},

abstract = {As the demand for socially intelligent Virtual Humans (VHs) increases, so follows the demand for effective and efficient cross-discipline collaboration that is required to bring these VHs “to life”. One avenue for increasing cross-discipline fluency is the aggregation and organization of seemingly disparate areas of research and development (e.g., graphics and emotion models) that are essential to the field of VH research. Our initial investigation (1) identifies and catalogues research streams concentrated in three multidisciplinary VH topic clusters within the domain of social intelligence, Emotion, Social Behavior, and The Face, (2) brings to the forefront key themes and prolific authors within each topic cluster, and (3) provides evidence that a full scoping review is warranted to further map the field, aggregate research findings, and identify gaps in the research. To enable collaboration, we provide full access to the refined VH cluster datasets, key word and author word clouds, as well as interactive evidence maps.},

keywords = {DTIC, UARC, VHTL, Virtual Humans},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{hartholt_re-architecting_2022,

title = {Re-architecting the virtual human toolkit: towards an interoperable platform for embodied conversational agent research and development},

author = {Arno Hartholt and Ed Fast and Zongjian Li and Kevin Kim and Andrew Leeds and Sharon Mozgai},

url = {https://dl.acm.org/doi/10.1145/3514197.3549671},

doi = {10.1145/3514197.3549671},

isbn = {978-1-4503-9248-8},

year  = {2022},

date = {2022-09-01},

urldate = {2022-09-15},

booktitle = {Proceedings of the 22nd ACM International Conference on Intelligent Virtual Agents},

pages = {1–8},

publisher = {ACM},

address = {Faro Portugal},

keywords = {DTIC, UARC, VHTL, Virtual Humans},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{mozgai_toward_2022,

title = {Toward a Semi-Automated Scoping Review of Virtual Human Smiles},

author = {Sharon Mozgai and Jade Winn and Cari Kaurloto and Andrew Leeds and Dirk Heylen and Arno Hartholt},

url = {http://www.lrec-conf.org/proceedings/lrec2022/workshops/SmiLa/index.html},

year  = {2022},

date = {2022-06-01},

booktitle = {Proceedings of the Smiling and Laughter across Contexts and the Life-span Workshop},

keywords = {DTIC, UARC, VHTL, Virtual Humans},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{hartholt_demonstrating_2022,

title = {Demonstrating the Rapid Integration & Development Environment (RIDE): Embodied Conversational Agent (ECA) and Multiagent Capabilities},

author = {Arno Hartholt and Ed Fast and Andrew Leeds and Kevin Kim and Andrew Gordon and Kyle McCullough and Volkan Ustun and Sharon Mozgai},

isbn = {978-1-4503-9213-6},

year  = {2022},

date = {2022-05-01},

urldate = {2022-09-20},

booktitle = {Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems},

pages = {1902–1904},

publisher = {International Foundation for Autonomous Agents and Multiagent Systems},

address = {Richland, SC},

series = {AAMAS '22},

abstract = {We demonstrate the Rapid Integration & Development Environment (RIDE), a research and development platform that enables rapid prototyping in support of multiagents and embodied conversational agents. RIDE is based on commodity game engines and includes a flexible architecture, system interoperability, and native support for artificial intelligence and machine learning frameworks.},

keywords = {AI, DTIC, Integration Technology, Machine Learning, UARC, VHTL, Virtual Humans},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{hartholt_rapid_2021,

title = {Rapid Prototyping for Simulation and Training with the Rapid Integration & Development Environment (RIDE)},

author = {Arno Hartholt and Kyle McCullough and Ed Fast and Andrew Leeds and Sharon Mozgai and Tim Aris and Volkan Ustun and Andrew Gordon and Christopher McGroarty},

year  = {2021},

date = {2021-11-01},

keywords = {AI, DTIC, Integration Technology, Machine Learning, Simulation, UARC, VHTL},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{mozgai_building_2021,

title = {Building BRAVEMIND Vietnam: User-Centered Design for Virtual Reality Exposure Therapy},

author = {Sharon Mozgai and Andrew Leeds and David Kwok and Ed Fast and Albert Skip Rizzo and Arno Hartholt},

doi = {10.1109/AIVR52153.2021.00056},

year  = {2021},

date = {2021-11-01},

booktitle = {2021 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR)},

pages = {247–250},

abstract = {There has been a recent resurgence of Vietnam-era Veterans seeking Veteran Affairs (VA) services for post-traumatic stress disorder (PTSD). Multiple studies have reported positive outcomes using Virtual Reality Exposure Therapy (VRET) with Iraq/Afghanistan Veteran PTSD patients, but there have been fewer investigations into the acceptability and feasibility of VRET with older Veterans. We have extended an established VRET system, BRAVEMIND, to include Vietnam relevant content following a user-centered iterative design methodology. This paper will present the BRAVEMIND Vietnam VRET system, including setup, content, and technical architecture along with the findings of an initial focus group with Vietnam Veterans. These Veterans rated this system to be acceptable as a treatment tool for combat-related PTSD and provided valuable first-person accounts of their time in Vietnam to help guide the evolution of the VR content.},

keywords = {DTIC, MedVR, VHTL, VR},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{hartholt_introducing_2021-1,

title = {Introducing VHMason: A Visual, Integrated, Multimodal Virtual Human Authoring Tool},

author = {Arno Hartholt and Ed Fast and Andrew Leeds and Sharon Mozgai},

url = {https://dl.acm.org/doi/10.1145/3472306.3478363},

doi = {10.1145/3472306.3478363},

isbn = {978-1-4503-8619-7},

year  = {2021},

date = {2021-09-01},

urldate = {2023-03-31},

booktitle = {Proceedings of the 21st ACM International Conference on Intelligent Virtual Agents},

pages = {109–111},

publisher = {Association for Computing Machinery},

address = {New York, NY, USA},

series = {IVA '21},

abstract = {A major impediment to the success of virtual agents is the inability of non-technical experts to easily author content. To address this barrier we present VHMason, a multimodal authoring tool designed to help creative authors build embodied conversational agents. We introduce the novel aspects of this authoring tool and explore a use case of the creation of an agent-led educational experience implemented at Children's Hospital Los Angeles (CHLA).},

keywords = {UARC, VHTL, Virtual Humans},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{hartholt_introducing_2020,

title = {Introducing Canvas: Combining Nonverbal Behavior Generation with User-Generated Content to Rapidly Create Educational Videos},

author = {Arno Hartholt and Adam Reilly and Ed Fast and Sharon Mozgai},

url = {https://dl.acm.org/doi/10.1145/3383652.3423880},

doi = {10.1145/3383652.3423880},

isbn = {978-1-4503-7586-3},

year  = {2020},

date = {2020-10-01},

booktitle = {Proceedings of the 20th ACM International Conference on Intelligent Virtual Agents},

pages = {1–3},

publisher = {ACM},

address = {Virtual Event Scotland UK},

abstract = {Rapidly creating educational content that is effective, engaging, and low-cost is a challenge. We present Canvas, a tool for educators that addresses this challenge by enabling the generation of educational video, led by an intelligent virtual agent, that combines rapid nonverbal behavior generation techniques with end-user facing authoring tools. With Canvas, educators can easily produce compelling educational videos with a minimum of investment by leveraging existing content provided by the tool (e.g., characters and environments) while incorporating their own custom content (e.g., images and video clips). Canvas has been delivered to the Smithsonian Science Education Center and is currently being evaluated internally before wider release. We discuss the system, feature set, design process, and lessons learned.},

keywords = {VHTL, Virtual Humans},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{mozgai_iterative_2020,

title = {Iterative Participatory Design for VRET Domain Transfer: From Combat Exposure to Military Sexual Trauma},

author = {Sharon Mozgai and Arno Hartholt and Andrew Leeds and Albert ‘Skip’ Rizzo},

url = {https://dl.acm.org/doi/abs/10.1145/3334480.3375219},

doi = {10.1145/3334480.3375219},

year  = {2020},

date = {2020-04-01},

booktitle = {Proceedings of the 2020 CHI Conference of Human Factors in Computing Systems},

pages = {8},

publisher = {ACM},

address = {Honolulu, HI},

abstract = {This case study describes the expansion of the BRAVEMIND virtual reality exposure therapy (VRET) system from the domain of combat-related posttraumatic stress disorder (PTSD) to the domain of PTSD due to Military Sexual Trauma (MST). As VRET continues to demonstrate efficacy in treating PTSD across multiple trauma types and anxiety disorders, adapting existing systems and content to new domains while simultaneously maintaining clinical integrity is becoming a high priority. To develop BRAVEMIND-MST we engaged in an iterative participatory design process with psychologists, engineers, and artists. This first-person account of our collaborative development process focuses on three key areas (1) VR Environment, (2) User-Avatar State, and (3) Events, while detailing the challenges we encountered and lessons learned. This process culminated in eight design guidelines as a first-step in defining a VRET domain transfer methodology.},

keywords = {MedVR, VHTL, Virtual Humans},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{mozgai_passive_2020,

title = {The Passive Sensing Agent: A Multimodal Adaptive mHealth Application},

author = {Sharon Mozgai and Arno Hartholt and Albert Rizzo},

url = {https://ieeexplore.ieee.org/document/9156177/},

doi = {10.1109/PerComWorkshops48775.2020.9156177},

isbn = {978-1-72814-716-1},

year  = {2020},

date = {2020-03-01},

booktitle = {Proceedings of the 2020 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)},

pages = {1–3},

publisher = {IEEE},

address = {Austin, TX, USA},

abstract = {We are demoing the Passive Sensing Agent (PSA), an mHealth virtual human coach, that collects multimodal data through passive sensors native to popular wearables (e.g., Apple Watch, FitBit, and Garmin). This virtual human interface delivers adaptive multi-media content via smartphone application that is specifically tailored to the user in the interdependent domains of physical, cognitive, and emotional health. Initially developed for the military, the PSA delivers health interventions (e.g., educational exercises, physical challenges, and performance feedback) matched to the individual user via novel adaptive logic-based algorithms while employing various behavior change techniques (e.g., goal-setting, barrier identification, rewards, modeling, etc.). A virtual human coach leads all interactions including the firsttime user experience and the brief daily sessions. All interactions were specifically designed to engage and motivate the user while continuously collecting data on their cognitive, emotional, and physical fitness. This multi-component application is integrated and deployed on an iPhone and Apple Watch prototype; a civilian version is currently in-development.},

keywords = {MedVR, UARC, VHTL, Virtual Humans},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{mozgai_adaptive_2020,

title = {An Adaptive Agent-Based Interface for Personalized Health Interventions},

author = {Sharon Mozgai and Arno Hartholt and Albert "Skip" Rizzo},

url = {https://dl.acm.org/doi/10.1145/3379336.3381467},

doi = {10.1145/3379336.3381467},

isbn = {978-1-4503-7513-9},

year  = {2020},

date = {2020-03-01},

booktitle = {Proceedings of the 25th International Conference on Intelligent User Interfaces Companion},

pages = {118–119},

publisher = {ACM},

address = {Cagliari Italy},

abstract = {This demo introduces a novel mHealth application with an agentbased interface designed to collect multimodal data with passive sensors native to popular wearables (e.g., Apple Watch, FitBit, and Garmin) as well as through user self-report. This mHealth application delivers personalized and adaptive multimedia content via smartphone application specifically tailored to the user in the interdependent domains of physical, cognitive, and emotional health via novel adaptive logic-based algorithms while employing behavior change techniques (e.g., goal-setting, barrier identification, etc.). A virtual human coach leads all interactions to improve adherence.},

keywords = {MedVR, UARC, VHTL, Virtual Humans},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{hartholt_ubiquitous_2019,

title = {Ubiquitous Virtual Humans: A Multi-platform Framework for Embodied AI Agents in XR},

author = {Arno Hartholt and Ed Fast and Adam Reilly and Wendy Whitcup and Matt Liewer and Sharon Mozgai},

url = {https://ieeexplore.ieee.org/document/8942321/},

doi = {10.1109/AIVR46125.2019.00072},

isbn = {978-1-72815-604-0},

year  = {2019},

date = {2019-12-01},

booktitle = {Proceedings of the 2019 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR)},

pages = {308–3084},

publisher = {IEEE},

address = {San Diego, CA, USA},

abstract = {We present an architecture and framework for the development of virtual humans for a range of computing platforms, including mobile, web, Virtual Reality (VR) and Augmented Reality (AR). The framework uses a mix of in-house and commodity technologies to support audio-visual sensing, speech recognition, natural language processing, nonverbal behavior generation and realization, text-to-speech generation, and rendering. This work builds on the Virtual Human Toolkit, which has been extended to support computing platforms beyond Windows. The resulting framework maintains the modularity of the underlying architecture, allows re-use of both logic and content through cloud services, and is extensible by porting lightweight clients. We present the current state of the framework, discuss how we model and animate our characters, and offer lessons learned through several use cases, including expressive character animation in seated VR, shared space and navigation in roomscale VR, autonomous AI in mobile AR, and real-time user performance feedback based on mobile sensors in headset AR.},

keywords = {UARC, VHTL, Virtual Humans},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{hartholt_virtual_2019,

title = {Virtual Humans in Augmented Reality: A First Step towards Real-World Embedded Virtual Roleplayers},

author = {Arno Hartholt and Sharon Mozgai and Ed Fast and Matt Liewer and Adam Reilly and Wendy Whitcup and Albert "Skip" Rizzo},

url = {http://dl.acm.org/citation.cfm?doid=3349537.3352766},

doi = {10.1145/3349537.3352766},

isbn = {978-1-4503-6922-0},

year  = {2019},

date = {2019-10-01},

booktitle = {Proceedings of the 7th International Conference on Human-Agent Interaction - HAI '19},

pages = {205–207},

publisher = {ACM Press},

address = {Kyoto, Japan},

abstract = {We present one of the first applications of virtual humans in Augmented Reality (AR), which allows young adults with Autism Spectrum Disorder (ASD) the opportunity to practice job interviews. It uses the Magic Leap’s AR hardware sensors to provide users with immediate feedback on six different metrics, including eye gaze, blink rate and head orientation. The system provides two characters, with three conversational modes each. Ported from an existing desktop application, the main development lessons learned were: 1) provide users with navigation instructions in the user interface, 2) avoid dark colors as they are rendered transparently, 3) use dynamic gaze so characters maintain eye contact with the user, 4) use hardware sensors like eye gaze to provide user feedback, and 5) use surface detection to place characters dynamically in the world.},

keywords = {MedVR, VHTL, Virtual Humans},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{hartholt_virtual_2019-1,

title = {Virtual Job Interviewing Practice for High-Anxiety Populations},

author = {Arno Hartholt and Sharon Mozgai and Albert "Skip" Rizzo},

url = {http://dl.acm.org/citation.cfm?doid=3308532.3329417},

doi = {10.1145/3308532.3329417},

isbn = {978-1-4503-6672-4},

year  = {2019},

date = {2019-07-01},

booktitle = {Proceedings of the 19th ACM International Conference on Intelligent Virtual Agents - IVA '19},

pages = {238–240},

publisher = {ACM Press},

address = {Paris, France},

abstract = {We present a versatile system for training job interviewing skills that focuses specifically on segments of the population facing increased challenges during the job application process. In particular, we target those with Autism Spectrum Disorder (ADS), veterans transitioning to civilian life, and former convicts integrating back into society. The system itself follows the SAIBA framework and contains several interviewer characters, who each represent a different type of vocational field, (e.g. service industry, retail, office, etc.) Each interviewer can be set to one of three conversational modes, which not only affects what they say and how they say it, but also their supporting body language. This approach offers varying difficulties, allowing users to start practicing with interviewers who are more encouraging and accommodating before moving on to personalities that are more direct and indifferent. Finally, the user can place the interviewers in different environmental settings (e.g. conference room, restaurant, executive office, etc.), allowing for many different combinations in which to practice.},

keywords = {MedVR, VHTL, Virtual Humans},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{mell_towards_2018,

title = {Towards a Repeated Negotiating Agent that Treats People Individually: Cooperation, Social Value Orientation, & Machiavellianism},

author = {Johnathan Mell and Gale Lucas and Sharon Mozgai and Jill Boberg and Ron Artstein and Jonathan Gratch},

url = {https://dl.acm.org/citation.cfm?id=3267910},

doi = {10.1145/3267851.3267910},

isbn = {ISBN: 978-1-4503-6013-5},

year  = {2018},

date = {2018-11-01},

booktitle = {Proceedings of the 18th International Conference on Intelligent Virtual Agents},

pages = {125–132},

publisher = {ACM},

address = {Sydney, Australia},

abstract = {We present the results of a study in which humans negotiate with computerized agents employing varied tactics over a repeated number of economic ultimatum games. We report that certain agents are highly effective against particular classes of humans: several individual difference measures for the human participant are shown to be critical in determining which agents will be successful. Asking for favors works when playing with pro-social people but backfires with more selfish individuals. Further, making poor offers invites punishment from Machiavellian individuals. These factors may be learned once and applied over repeated negotiations, which means user modeling techniques that can detect these differences accurately will be more successful than those that don’t. Our work additionally shows that a significant benefit of cooperation is also present in repeated games—after sufficient interaction. These results have deep significance to agent designers who wish to design agents that are effective in negotiating with a broad swath of real human opponents. Furthermore, it demonstrates the effectiveness of techniques which can reason about negotiation over time.},

keywords = {VHTL, Virtual Humans},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{neubauer_relationship_2017,

title = {The relationship between task-induced stress, vocal changes, and physiological state during a dyadic team task},

author = {Catherine Neubauer and Mathieu Chollet and Sharon Mozgai and Mark Dennison and Peter Khooshabeh and Stefan Scherer},

url = {http://dl.acm.org/citation.cfm?doid=3136755.3136804},

doi = {10.1145/3136755.3136804},

isbn = {978-1-4503-5543-8},

year  = {2017},

date = {2017-11-01},

booktitle = {Proceedings of the 19th ACM International Conference on Multimodal Interaction},

pages = {426–432},

publisher = {ACM Press},

address = {Glasgow, UK},

abstract = {It is commonly known that a relationship exists between the human voice and various emotional states. Past studies have demonstrated changes in a number of vocal features, such as fundamental frequency f0 and peakSlope, as a result of varying emotional state. These voice characteristics have been shown to relate to emotional load, vocal tension, and, in particular, stress. Although much research exists in the domain of voice analysis, few studies have assessed the relationship between stress and changes in the voice during a dyadic team interaction. The aim of the present study was to investigate the multimodal interplay between speech and physiology during a high-workload, high-stress team task. Specifically, we studied task-induced effects on participants' vocal signals, specifically, the f0 and peakSlope features, as well as participants' physiology, through cardiovascular measures. Further, we assessed the relationship between physiological states related to stress and changes in the speaker's voice. We recruited participants with the specific goal of working together to diffuse a simulated bomb. Half of our sample participated in an "Ice Breaker" scenario, during which they were allowed to converse and familiarize themselves with their teammate prior to the task, while the other half of the sample served as our "Control". Fundamental frequency (f0), peakSlope, physiological state, and subjective stress were measured during the task. Results indicated that f0 and peakSlope significantly increased from the beginning to the end of each task trial, and were highest in the last trial, which indicates an increase in emotional load and vocal tension. Finally, cardiovascular measures of stress indicated that the vocal and emotional load of speakers towards the end of the task mirrored a physiological state of psychological "threat".},

keywords = {ARL, DoD, UARC, VHTL, Virtual Humans},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{ringeval_summary_2017,

title = {Summary for AVEC 2017: Real-life Depression and Affect Challenge and Workshop},

author = {Fabien Ringeval and Björn Schuller and Michel Valstar and Jonathan Gratch and Roddy Cowie and Maja Pantic},

url = {http://dl.acm.org/citation.cfm?doid=3123266.3132049},

doi = {10.1145/3123266.3132049},

isbn = {978-1-4503-4906-2},

year  = {2017},

date = {2017-10-01},

booktitle = {Proceedings of the 2017 ACM on Multimedia Conference},

pages = {1963–1964},

publisher = {ACM Press},

address = {Mountain View, CA},

abstract = {The seventh Audio-Visual Emotion Challenge and workshop AVEC 2017 was held in conjunction with ACM Multimedia'17. This year, the AVEC series addresses two distinct sub-challenges: emotion recognition and depression detection. The Affect Sub-Challenge is based on a novel dataset of human-human interactions recorded 'in-the-wild', whereas the Depression Sub-Challenge is based on the same dataset as the one used in AVEC 2016, with human-agent interactions. In this summary, we mainly describe participation and its conditions.},

keywords = {UARC, VHTL, Virtual Humans},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{mozgai_tell_2017,

title = {To Tell the Truth: Virtual Agents and Morning Morality},

author = {Sharon Mozgai and Gale Lucas and Jonathan Gratch},

url = {http://link.springer.com/10.1007/978-3-319-67401-8_37},

doi = {10.1007/978-3-319-67401-8_37},

isbn = {978-3-319-67400-1 978-3-319-67401-8},

year  = {2017},

date = {2017-08-01},

booktitle = {Proceedings of the 17th International Conference on Intelligent Virtual Agents},

pages = {283–286},

publisher = {Springer International Publishing},

address = {Stockholm, Sweden},

abstract = {This paper investigates the impact of time of day on truthfulness in human-agent interactions. Time of day has been found to have important implications for moral behavior in human-human interaction. Namely, the morning morality effect shows that people are more likely to act ethically (i.e., tell fewer lies) in the morning than in the afternoon. Based on previous work on disclosure and virtual agents, we propose that this effect will not bear out in human-agent interactions. Preliminary evaluation shows that individuals who lie when engaged in multi-issue bargaining tasks with the Conflict Resolution Agent, a semi-automated virtual human, tell more lies to human negotiation partners than virtual agent negotiation partners in the afternoon and are more likely to tell more lies in the afternoon than in the morning when they believe they are negotiating with a human. Time of day does not have a significant effect on the amount of lies told to the virtual agent during the multi-issue bargaining task.},

keywords = {UARC, VHTL, Virtual Humans},

pubstate = {published},

tppubtype = {inproceedings}

}