Publications

@article{leitner_designing_2023,

title = {Designing Game-Based Learning for High School Artificial Intelligence Education},

author = {Maxyn Leitner and Eric Greenwald and Ning Wang and Ryan Montgomery and Chirag Merchant},

url = {https://link.springer.com/10.1007/s40593-022-00327-w},

doi = {10.1007/s40593-022-00327-w},

issn = {1560-4292, 1560-4306},

year  = {2023},

date = {2023-06-01},

urldate = {2023-09-20},

journal = {Int J Artif Intell Educ},

volume = {33},

number = {2},

pages = {384–398},

abstract = {Abstract 

 Artificial Intelligence (AI) permeates every aspect of our daily lives and is no longer a subject reserved for a select few in higher education but is essential knowledge that our youth need for the future. Much is unknown about the level of AI knowledge that is age and developmentally appropriate for high school, let alone about how to teach AI to even younger learners. In this theoretical paper, we discuss the design of a game-based learning environment for high school AI education, drawing upon insights gained from a prior cognitive interview study at a STEM focused private high school. We argue that game-based learning is an excellent fit for AI education due to the commonality of problem solving in both game playing and AI.},

keywords = {AI, DTIC, Virtual Humans},

pubstate = {published},

tppubtype = {article}

}

@article{rodrigues_multidimensional_2023,

title = {A multidimensional taxonomy for human-robot interaction in construction},

author = {Patrick B. Rodrigues and Rashmi Singh and Mert Oytun and Pooya Adami and Peter J. Woods and Burcin Becerik-Gerber and Lucio Soibelman and Yasemin Copur-Gencturk and Gale M. Lucas},

url = {https://www.sciencedirect.com/science/article/pii/S092658052300105X},

doi = {10.1016/j.autcon.2023.104845},

issn = {0926-5805},

year  = {2023},

date = {2023-06-01},

urldate = {2023-03-31},

journal = {Automation in Construction},

volume = {150},

pages = {104845},

abstract = {Despite the increased interest in construction robotics both in academia and the industry, insufficient attention has been given to aspects related to Human-Robot Interaction (HRI). Characterizing HRI for construction tasks can help researchers organize knowledge in a structured manner that allows for classifying construction robotics applications and comparing and benchmarking different studies. This paper builds upon existing taxonomies and empirical studies in HRI in various industries (e.g., construction, manufacturing, and military, among others) to propose a multidimensional taxonomy to characterize HRI applications in the construction industry. The taxonomy design followed a systematic literature review in which common themes were identified and grouped into 16 categories. The proposed taxonomy can be used as a foundation for systematic reviews and meta-analyses of HRI applications in construction and can benefit the construction industry by informing the design of collaborative tasks performed by human-robot teams.},

keywords = {DTIC, UARC, Virtual Humans},

pubstate = {published},

tppubtype = {article}

}

@article{aris_learning_2023,

title = {Learning to Take Cover with Navigation-Based Waypoints via Reinforcement Learning},

author = {Timothy Aris and Volkan Ustun and Rajay Kumar},

url = {https://journals.flvc.org/FLAIRS/article/view/133348},

doi = {10.32473/flairs.36.133348},

issn = {2334-0762},

year  = {2023},

date = {2023-05-01},

urldate = {2023-08-04},

journal = {FLAIRS},

volume = {36},

abstract = {This paper presents a reinforcement learning model designed to learn how to take cover on geo-specific terrains, an essential behavior component for military training simulations. Training of the models is performed on the Rapid Integration and Development Environment (RIDE) leveraging the Unity ML-Agents framework. This work expands on previous work on raycast-based agents by increasing the number of enemies from one to three. We demonstrate an automated way of generating training and testing data within geo-specific terrains. We show that replacing the action space with a more abstracted, navmesh-based waypoint movement system can increase the generality and success rate of the models while providing similar results to our previous paper's results regarding retraining across terrains. We also comprehensively evaluate the differences between these and the previous models. Finally, we show that incorporating pixels into the model's input can increase performance at the cost of longer training times.},

keywords = {CogArch, Cognitive Architecture, DTIC, UARC, Virtual Humans},

pubstate = {published},

tppubtype = {article}

}

@article{murawski_transforming_2023,

title = {Transforming a Negotiation Framework to Resolve Conflicts among Older Adults and Family Caregivers},

author = {Alaine Murawski and Vanessa Ramirez-Zohfeld and Allison Schierer and Charles Olvera and Johnathan Mell and Jonathan Gratch and Jeanne Brett and Lee A. Lindquist},

url = {https://www.mdpi.com/2308-3417/8/2/36},

doi = {10.3390/geriatrics8020036},

issn = {2308-3417},

year  = {2023},

date = {2023-04-01},

urldate = {2023-03-31},

journal = {Geriatrics},

volume = {8},

number = {2},

pages = {36},

abstract = {Background: Family caregivers of older people with Alzheimer’s dementia (PWD) often need to advocate and resolve health-related conflicts (e.g., determining treatment necessity, billing errors, and home health extensions). As they deal with these health system conflicts, family caregivers experience unnecessary frustration, anxiety, and stress. The goal of this research was to apply a negotiation framework to resolve real-world family caregiver–older adult conflicts. Methods: We convened an interdisciplinary team of national community-based family caregivers, social workers, geriatricians, and negotiation experts (n = 9; Illinois, Florida, New York, and California) to examine the applicability of negotiation and conflict management frameworks to three older adult–caregiver conflicts (i.e., caregiver–older adult, caregiver–provider, and caregiver–caregiver). The panel of caregivers provided scenarios and dialogue describing conflicts they experienced in these three settings. A qualitative analysis was then performed grouping the responses into a framework matrix. Results: Upon presenting the three conflicts to the caregivers, 96 responses (caregiver–senior), 75 responses (caregiver–caregiver), and 80 responses (caregiver–provider) were generated. A thematic analysis showed that the statements and responses fit the interest–rights–power (IRP) negotiation framework. Discussion: The interests–rights–power (IRP) framework, used in business negotiations, provided insight into how caregivers experienced conflict with older adults, providers, and other caregivers. Future research is needed to examine applying the IRP framework in the training of caregivers of older people with Alzheimer’s dementia.},

note = {Number: 2 

Publisher: Multidisciplinary Digital Publishing Institute},

keywords = {DTIC, UARC, Virtual Humans},

pubstate = {published},

tppubtype = {article}

}

@article{de_melo_social_2023,

title = {Social Functions of Machine Emotional Expressions},

author = {Celso M. De Melo and Jonathan Gratch and Stacy Marsella and Catherine Pelachaud},

url = {https://ieeexplore.ieee.org/document/10093227/},

doi = {10.1109/JPROC.2023.3261137},

issn = {0018-9219, 1558-2256},

year  = {2023},

date = {2023-04-01},

urldate = {2023-08-04},

journal = {Proc. IEEE},

pages = {1–16},

keywords = {DTIC, UARC, Virtual Humans},

pubstate = {published},

tppubtype = {article}

}

@article{lu_co-speech_2023,

title = {Co-Speech Gesture Synthesis using Discrete Gesture Token Learning},

author = {Shuhong Lu and Youngwoo Yoon and Andrew Feng},

url = {https://arxiv.org/abs/2303.12822},

doi = {10.48550/ARXIV.2303.12822},

year  = {2023},

date = {2023-04-01},

urldate = {2023-08-04},

abstract = {Synthesizing realistic co-speech gestures is an important and yet unsolved problem for creating believable motions that can drive a humanoid robot to interact and communicate with human users. Such capability will improve the impressions of the robots by human users and will find applications in education, training, and medical services. One challenge in learning the co-speech gesture model is that there may be multiple viable gesture motions for the same speech utterance. The deterministic regression methods can not resolve the conflicting samples and may produce over-smoothed or damped motions. We proposed a two-stage model to address this uncertainty issue in gesture synthesis by modeling the gesture segments as discrete latent codes. Our method utilizes RQ-VAE in the first stage to learn a discrete codebook consisting of gesture tokens from training data. In the second stage, a two-level autoregressive transformer model is used to learn the prior distribution of residual codes conditioned on input speech context. Since the inference is formulated as token sampling, multiple gesture sequences could be generated given the same speech input using top-k sampling. The quantitative results and the user study showed the proposed method outperforms the previous methods and is able to generate realistic and diverse gesture motions.},

note = {Publisher: arXiv 

Version Number: 1},

keywords = {DTIC, UARC, Virtual Humans},

pubstate = {published},

tppubtype = {article}

}

@article{gratch_promise_2023,

title = {The promise and peril of interactive embodied agents for studying non-verbal communication: a machine learning perspective},

author = {Jonathan Gratch},

url = {https://royalsocietypublishing.org/doi/abs/10.1098/rstb.2021.0475},

doi = {10.1098/rstb.2021.0475},

year  = {2023},

date = {2023-03-01},

urldate = {2023-03-31},

journal = {Philosophical Transactions of the Royal Society B: Biological Sciences},

volume = {378},

number = {1875},

pages = {20210475},

abstract = {In face-to-face interactions, parties rapidly react and adapt to each other's words, movements and expressions. Any science of face-to-face interaction must develop approaches to hypothesize and rigorously test mechanisms that explain such interdependent behaviour. Yet conventional experimental designs often sacrifice interactivity to establish experimental control. Interactive virtual and robotic agents have been offered as a way to study true interactivity while enforcing a measure of experimental control by allowing participants to interact with realistic but carefully controlled partners. But as researchers increasingly turn to machine learning to add realism to such agents, they may unintentionally distort the very interactivity they seek to illuminate, particularly when investigating the role of non-verbal signals such as emotion or active-listening behaviours. Here I discuss some of the methodological challenges that may arise when machine learning is used to model the behaviour of interaction partners. By articulating and explicitly considering these commitments, researchers can transform ‘unintentional distortions’ into valuable methodological tools that yield new insights and better contextualize existing experimental findings that rely on learning technology. 

This article is part of a discussion meeting issue ‘Face2face: advancing the science of social interaction’.},

note = {Publisher: Royal Society},

keywords = {DTIC, UARC, Virtual Humans},

pubstate = {published},

tppubtype = {article}

}

@article{awada_ten_2023,

title = {Ten questions concerning the impact of environmental stress on office workers},

author = {Mohamad Awada and Burcin Becerik-Gerber and Ruying Liu and Mirmahdi Seyedrezaei and Zheng Lu and Matheos Xenakis and Gale Lucas and Shawn C. Roll and Shrikanth Narayanan},

url = {https://www.sciencedirect.com/science/article/pii/S0360132322011945},

doi = {10.1016/j.buildenv.2022.109964},

issn = {0360-1323},

year  = {2023},

date = {2023-02-01},

urldate = {2023-03-31},

journal = {Building and Environment},

volume = {229},

pages = {109964},

abstract = {We regularly face stress during our everyday activities, to the extent that stress is recognized by the World Health Organization as the epidemic of the 21st century. Stress is how humans respond physically and psychologically to adjustments, experiences, conditions, and circumstances in their lives. While there are many reasons for stress, work and job pressure remain the main cause. Thus, companies are increasingly interested in creating healthier, more comfortable, and stress-free offices for their workers. The indoor environment can induce environmental stress when it cannot satisfy the individual needs for health and comfort. In fact, office environmental conditions (e.g., thermal, and indoor air conditions, lighting, and noise) and interior design parameters (e.g., office layout, colors, furniture, access to views, distance to window, personal control and biophilic design) have been found to affect office workers' stress levels. A line of research based on the stress recovery theory offers new insights for establishing offices that limit environmental stress and help with work stress recovery. To that end, this paper answers ten questions that explore the relation between the indoor office-built environment and stress levels among workers. The answers to the ten questions are based on an extensive literature review to draw conclusions from what has been achieved to date. Thus, this study presents a foundation for future environmental stress related research in offices.},

keywords = {DTIC, UARC, Virtual Humans},

pubstate = {published},

tppubtype = {article}

}

@article{lucas_customizing_2023,

title = {Customizing virtual interpersonal skills training applications may not improve trainee performance},

author = {Gale M. Lucas and Johnathan Mell and Jill Boberg and Forrest Zenone and Ewart J. Visser and Chad Tossell and Todd Seech},

url = {https://www.nature.com/articles/s41598-022-27154-2},

doi = {10.1038/s41598-022-27154-2},

issn = {2045-2322},

year  = {2023},

date = {2023-01-01},

urldate = {2023-03-31},

journal = {Sci Rep},

volume = {13},

number = {1},

pages = {78},

abstract = {While some theoretical perspectives imply that the context of a virtual training should be customized to match the intended context where those skills would ultimately be applied, others suggest this might not be necessary for learning. It is important to determine whether manipulating context matters for performance in training applications because customized virtual training systems made for specific use cases are more costly than generic “off-the-shelf” ones designed for a broader set of users. Accordingly, we report a study where military cadets use a virtual platform to practice their negotiation skills, and are randomly assigned to one of two virtual context conditions: military versus civilian. Out of 28 measures capturing performance in the negotiation, there was only one significant result: cadets in the civilian condition politely ask the agent to make an offer significantly more than those in the military condition. These results imply that—for this interpersonal skills application, and perhaps ones like it—virtual context may matter very little for performance during social skills training, and that commercial systems may yield real benefits to military scenarios with little-to-no modification.},

note = {Number: 1 

Publisher: Nature Publishing Group},

keywords = {DTIC, UARC, Virtual Humans},

pubstate = {published},

tppubtype = {article}

}

@article{adami_participants_2023,

title = {Participants matter: Effectiveness of VR-based training on the knowledge, trust in the robot, and self-efficacy of construction workers and university students},

author = {Pooya Adami and Rashmi Singh and Patrick Borges Rodrigues and Burcin Becerik-Gerber and Lucio Soibelman and Yasemin Copur-Gencturk and Gale Lucas},

url = {https://www.sciencedirect.com/science/article/pii/S1474034622002956},

doi = {10.1016/j.aei.2022.101837},

issn = {1474-0346},

year  = {2023},

date = {2023-01-01},

urldate = {2023-03-31},

journal = {Advanced Engineering Informatics},

volume = {55},

pages = {101837},

abstract = {Virtual Reality (VR)-based training has gained attention from the scientific community in the Architecture, Engineering, and Construction (AEC) industry as a cost-effective and safe method that eliminates the safety risks that may impose on workers during the training compared to traditional training methods (e.g., in-person hands-on training, apprenticeship). Although researchers have developed VR-based training for construction workers, some have recruited students rather than workers to understand the effect of their VR-based training. However, students are different from construction workers in many ways, which can threaten the validity of such studies. Hence, research is needed to investigate the extent to which the findings of a VR-based training study are contingent on whether students or construction workers were used as the study sample. This paper strives to compare the effectiveness of VR-based training on university students’ and construction workers’ knowledge acquisition, trust in the robot, and robot operation self-efficacy in remote operation of a construction robot. Twenty-five construction workers and twenty-five graduate construction engineering students were recruited to complete a VR-based training for remote operating a demolition robot. We used quantitative analyses to answer our research questions. Our study shows that the results are dependent on the target sample in that students gained more knowledge, whereas construction workers gained more trust in the robot and more self-efficacy in robot operation. These findings suggest that the effectiveness of VR-based training on students may not necessarily associate with its effectiveness on construction workers.},

keywords = {DTIC, UARC, Virtual Humans},

pubstate = {published},

tppubtype = {article}

}

@article{chawla_towards_2023,

title = {Towards Emotion-Aware Agents for Improved User Satisfaction and Partner Perception in Negotiation Dialogues},

author = {Kushal Chawla and Rene Clever and Jaysa Ramirez and Gale M. Lucas and Jonathan Gratch},

url = {https://ieeexplore.ieee.org/abstract/document/10021626},

doi = {10.1109/TAFFC.2023.3238007},

issn = {1949-3045},

year  = {2023},

date = {2023-01-01},

journal = {IEEE Transactions on Affective Computing},

pages = {1–12},

abstract = {Negotiation is a complex social interaction that encapsulates emotional encounters in human decision-making. Virtual agents that can negotiate with humans by the means of language are useful in pedagogy and conversational AI. To advance the development of such agents, we explore the role of emotion in the prediction of two important subjective goals in a negotiation – outcome satisfaction and partner perception. We devise ways to measure and compare different degrees of emotion expression in negotiation dialogues, consisting of emoticon, lexical, and contextual variables. Through an extensive analysis of a large-scale dataset in chat-based negotiations, we find that incorporating emotion expression explains significantly more variance, above and beyond the demographics and personality traits of the participants. Further, our temporal analysis reveals that emotive information from both early and later stages of the negotiation contributes to this prediction, indicating the need for a continual learning model of capturing emotion for automated agents. Finally, we extend our analysis to another dataset, showing promise that our findings generalize to more complex scenarios. We conclude by discussing our insights, which will be helpful for designing adaptive negotiation agents that interact through realistic communication interfaces.},

note = {Conference Name: IEEE Transactions on Affective Computing},

keywords = {DTIC, UARC, Virtual Humans},

pubstate = {published},

tppubtype = {article}

}

@article{lei_emotional_2023,

title = {Emotional Expressivity is a Reliable Signal of Surprise},

author = {Su Lei and Jonathan Gratch},

doi = {10.1109/TAFFC.2023.3234015},

issn = {1949-3045},

year  = {2023},

date = {2023-01-01},

journal = {IEEE Transactions on Affective Computing},

pages = {1–12},

abstract = {We consider the problem of inferring what happened to a person in a social task from momentary facial reactions. To approach this, we introduce several innovations. First, rather than predicting what (observers think) someone feels, we predict objective features of the event that immediately preceded the facial reactions. Second, we draw on appraisal theory, a key psychological theory of emotion, to characterize features of this immediately-preceded event. Specifically, we explore if facial expressions reveal if the event is expected, goal-congruent, and norm-compatible. Finally, we argue that emotional expressivity serves as a better feature for characterizing momentary expressions than traditional facial features. Specifically, we use supervised machine learning to predict third-party judgments of emotional expressivity with high accuracy, and show this model improves inferences about the nature of the event that preceded an emotional reaction. Contrary to common sense, “genuine smiles” failed to predict if an event advanced a person's goals. Rather, expressions best revealed if an event violated expectations. We discussed the implications of these findings for the interpretation of facial displays and potential limitations that could impact the generality of these findings.},

note = {Conference Name: IEEE Transactions on Affective Computing},

keywords = {DTIC, UARC, Virtual Humans},

pubstate = {published},

tppubtype = {article}

}

@article{becerik-gerber_field_2022,

title = {The field of human building interaction for convergent research and innovation for intelligent built environments},

author = {Burcin Becerik-Gerber and Gale Lucas and Ashrant Aryal and Mohamad Awada and Mario Bergés and Sarah Billington and Olga Boric-Lubecke and Ali Ghahramani and Arsalan Heydarian and Christoph Höelscher and Farrokh Jazizadeh and Azam Khan and Jared Langevin and Ruying Liu and Frederick Marks and Matthew Louis Mauriello and Elizabeth Murnane and Haeyoung Noh and Marco Pritoni and Shawn Roll and Davide Schaumann and Mirmahdi Seyedrezaei and John E. Taylor and Jie Zhao and Runhe Zhu},

url = {https://www.nature.com/articles/s41598-022-25047-y},

doi = {10.1038/s41598-022-25047-y},

issn = {2045-2322},

year  = {2022},

date = {2022-12-01},

urldate = {2023-03-31},

journal = {Sci Rep},

volume = {12},

number = {1},

pages = {22092},

abstract = {Human-Building Interaction (HBI) is a convergent field that represents the growing complexities of the dynamic interplay between human experience and intelligence within built environments. This paper provides core definitions, research dimensions, and an overall vision for the future of HBI as developed through consensus among 25 interdisciplinary experts in a series of facilitated workshops. Three primary areas contribute to and require attention in HBI research: humans (human experiences, performance, and well-being), buildings (building design and operations), and technologies (sensing, inference, and awareness). Three critical interdisciplinary research domains intersect these areas: control systems and decision making, trust and collaboration, and modeling and simulation. Finally, at the core, it is vital for HBI research to center on and support equity, privacy, and sustainability. Compelling research questions are posed for each primary area, research domain, and core principle. State-of-the-art methods used in HBI studies are discussed, and examples of original research are offered to illustrate opportunities for the advancement of HBI research.},

note = {Number: 1 

Publisher: Nature Publishing Group},

keywords = {DTIC, UARC, Virtual Humans},

pubstate = {published},

tppubtype = {article}

}

@article{difede_enhancing_2022,

title = {Enhancing exposure therapy for posttraumatic stress disorder (PTSD): a randomized clinical trial of virtual reality and imaginal exposure with a cognitive enhancer},

author = {JoAnn Difede and Barbara O. Rothbaum and Albert A. Rizzo and Katarzyna Wyka and Lisa Spielman and Christopher Reist and Michael J. Roy and Tanja Jovanovic and Seth D. Norrholm and Judith Cukor and Megan Olden and Charles E. Glatt and Francis S. Lee},

url = {https://www.nature.com/articles/s41398-022-02066-x},

doi = {10.1038/s41398-022-02066-x},

issn = {2158-3188},

year  = {2022},

date = {2022-12-01},

urldate = {2022-09-13},

journal = {Transl Psychiatry},

volume = {12},

number = {1},

pages = {299},

abstract = {Abstract Posttraumatic stress disorder (PTSD) is a significant public health issue. Yet, there are limited treatment options and no data to suggest which treatment will work for whom. We tested the efficacy of virtual reality exposure (VRE) or prolonged imaginal exposure (PE), augmented with D-cycloserine (DCS) for combat-related PTSD. As an exploratory aim, we examined whether brain-derived neurotrophic factor (BDNF) and fatty acid amide hydrolase (FAAH) moderated treatment response. Military personnel with PTSD ( n = 192) were recruited into a multisite double-blind randomized controlled trial to receive nine weeks of VRE or PE, with DCS or placebo. Primary outcome was the improvement in symptom severity. Randomization was stratified by comorbid depression (MDD) and site. Participants in both VRE and PE showed similar meaningful clinical improvement with no difference between the treatment groups. A significant interaction ( p = 0.45) suggested VRE was more effective for depressed participants (CAPS difference M = 3.51 [95% CI 1.17–5.86]},

keywords = {DTIC, MedVR, Virtual Humans},

pubstate = {published},

tppubtype = {article}

}

@article{becerik-gerber_ten_2022,

title = {Ten questions concerning human-building interaction research for improving the quality of life},

author = {Burçin Becerik-Gerber and Gale Lucas and Ashrant Aryal and Mohamad Awada and Mario Bergés and Sarah L Billington and Olga Boric-Lubecke and Ali Ghahramani and Arsalan Heydarian and Farrokh Jazizadeh and Ruying Liu and Runhe Zhu and Frederick Marks and Shawn Roll and Mirmahdi Seyedrezaei and John E. Taylor and Christoph Höelscher and Azam Khan and Jared Langevin and Matthew Louis Mauriello and Elizabeth Murnane and Haeyoung Noh and Marco Pritoni and Davide Schaumann and Jie Zhao},

url = {https://www.sciencedirect.com/science/article/pii/S0360132322009118},

doi = {10.1016/j.buildenv.2022.109681},

issn = {0360-1323},

year  = {2022},

date = {2022-12-01},

urldate = {2023-03-31},

journal = {Building and Environment},

volume = {226},

pages = {109681},

abstract = {This paper seeks to address ten questions that explore the burgeoning field of Human-Building Interaction (HBI), an interdisciplinary field that represents the next frontier in convergent research and innovation to enable the dynamic interplay of human and building interactional intelligence. The field of HBI builds on several existing efforts in historically separate research fields/communities and aims to understand how buildings affect human outcomes and experiences, as well as how humans interact with, adapt to, and affect the built environment and its systems, to support buildings that can learn, enable adaptation, and evolve at different scales to improve the quality-of-life of its users while optimizing resource usage and service availability. Questions were developed by a diverse group of researchers with backgrounds in design, engineering, computer science, social science, and health science. Answers to these questions draw conclusions from what has been achieved to date as reported in the available literature and establish a foundation for future HBI research. This paper aims to encourage interdisciplinary collaborations in HBI research to change the way people interact with and perceive technology within the context of buildings and inform the design, construction, and operation of next-generation, intelligent built environments. In doing so, HBI research can realize a myriad of benefits for human users, including improved productivity, health, cognition, convenience, and comfort, all of which are essential to societal well-being.},

keywords = {DTIC, UARC, Virtual Humans},

pubstate = {published},

tppubtype = {article}

}

@article{pauw_avatar_2022,

title = {The avatar will see you now: Support from a virtual human provides socio-emotional benefits},

author = {Lisanne S. Pauw and Disa A. Sauter and Gerben A. Kleef and Gale M. Lucas and Jonathan Gratch and Agneta H. Fischer},

url = {https://linkinghub.elsevier.com/retrieve/pii/S074756322200190X},

doi = {10.1016/j.chb.2022.107368},

issn = {07475632},

year  = {2022},

date = {2022-11-01},

urldate = {2022-09-28},

journal = {Computers in Human Behavior},

volume = {136},

pages = {107368},

keywords = {DTIC, Virtual Humans},

pubstate = {published},

tppubtype = {article}

}

@article{gratch_power_2022,

title = {The power to harm: AI assistants pave the way to unethical behavior},

author = {Jonathan Gratch and Nathanael J. Fast},

url = {https://linkinghub.elsevier.com/retrieve/pii/S2352250X22001014},

doi = {10.1016/j.copsyc.2022.101382},

issn = {2352250X},

year  = {2022},

date = {2022-10-01},

urldate = {2022-09-28},

journal = {Current Opinion in Psychology},

volume = {47},

pages = {101382},

keywords = {AI, DTIC, Virtual Humans},

pubstate = {published},

tppubtype = {article}

}

@article{de_melo_heuristic_2022,

title = {Heuristic thinking and altruism toward machines in people impacted by COVID-19},

author = {Celso Melo and Jonathan Gratch and Frank Krueger},

url = {http://www.thieme-connect.de/DOI/DOI?10.1055/s-0042-1742544},

doi = {10.1055/s-0042-1742544},

issn = {0943-4747, 2364-0502},

year  = {2022},

date = {2022-08-01},

urldate = {2023-03-31},

journal = {Yearb Med Inform},

volume = {31},

number = {1},

pages = {226–227},

abstract = {he authors conducted a study of how human interaction with machines needs to be studied, given the advent of intelligent systems in everyday life (such as autonomous vehicles) and how COVID-19 experiences shape human altruistic responses to machines. The authors correctly claim that more study of how humans can collaborate, and their attitudes and behavior toward machines differs from social norms with humans. They make use of the ‘Computers as Social Actors’ theory of Reeves and Nass (1996), which was influential in human computer and robot interaction research. It argues that people heuristically treat machines like people, and that encouraging intuitive thinking, in contrast to deliberation, led to increased cooperation in non-strategic settings. The authors are the first to apply and test this with concrete cognitive studies. The dictator game is used to measure altruism; the user has options to give tokens to another user (in this case the computer or a ‘human’ (both delivered by computer message to obscure the source). 186 participants were used as senders, across 40 US states, and provided a diverse sample. They were administered the abbreviated Post-Traumatic Stress Disorder (PTSD) checklist (to measure COVID-19 impact), and three subjective scales to gain insight on mechanisms. These were the Cognitive Reflection test to measure if those impacted engage in reduced reflection, i.e., more intuitive thinking, the Faith in Technology scale, and the Moral Foundations Questionnaire. Results showed a reduction in the usual bias against fairness toward machines the more the user had been impacted by COVID-19. There were also sharp increases in intuitive (and incorrect) thinking and faith in technology among the most highly affected group. The authors through multiple mediation analysis showed that faith in technology and heuristic thinking mediate the offer bias. They also caution that in times of stress the disproportional impact of COVID-19 on vulnerable groups leads to the need for ethical guidelines and regulations to ensure altruism/cooperation shown to machines is well deserved. They also point out the factors such as individual stress propensity, education level, and socioeconomic status could make individuals susceptible to heuristic thinking, and other social norms such as reciprocity, trust and fairness may also shape collaboration with machines.},

note = {Publisher: Georg Thieme Verlag KG},

keywords = {UARC, Virtual Humans},

pubstate = {published},

tppubtype = {article}

}

@article{awada_cognitive_2022,

title = {Cognitive performance, creativity and stress levels of neurotypical young adults under different white noise levels},

author = {Mohamad Awada and Burcin Becerik-Gerber and Gale Lucas and Shawn Roll},

url = {https://www.nature.com/articles/s41598-022-18862-w},

doi = {10.1038/s41598-022-18862-w},

issn = {2045-2322},

year  = {2022},

date = {2022-08-01},

urldate = {2023-03-31},

journal = {Sci Rep},

volume = {12},

number = {1},

pages = {14566},

abstract = {Noise is often considered a distractor; however recent studies suggest that sub-attentive individuals or individuals diagnosed with attention deficit hyperactivity disorder can benefit from white noise to enhance their cognitive performance. Research regarding the effect of white noise on neurotypical adults presents mixed results, thus the implications of white noise on the neurotypical population remain unclear. Thus, this study investigates the effect of 2 white noise conditions, white noise level at 45 dB and white noise level at 65 dB, on the cognitive performance, creativity, and stress levels of neurotypical young adults in a private office space. These conditions are compared to a baseline condition where participants are exposed to the office ambient noise. Our findings showed that the white noise level at 45 dB resulted in better cognitive performance in terms of sustained attention, accuracy, and speed of performance as well as enhanced creativity and lower stress levels. On the other hand, the 65 dB white noise condition led to improved working memory but higher stress levels, which leads to the conclusion that different tasks might require different noise levels for optimal performance. These results lay the foundation for the integration of white noise into office workspaces as a tool to enhance office workers’ performance.},

note = {Number: 1 

Publisher: Nature Publishing Group},

keywords = {UARC, Virtual Humans},

pubstate = {published},

tppubtype = {article}

}

@article{adami_impact_2022,

title = {Impact of VR-Based Training on Human–Robot Interaction for Remote Operating Construction Robots},

author = {Pooya Adami and Patrick B. Rodrigues and Peter J. Woods and Burcin Becerik-Gerber and Lucio Soibelman and Yasemin Copur-Gencturk and Gale Lucas},

url = {https://ascelibrary.org/doi/10.1061/%28ASCE%29CP.1943-5487.0001016},

doi = {10.1061/(ASCE)CP.1943-5487.0001016},

issn = {0887-3801, 1943-5487},

year  = {2022},

date = {2022-05-01},

urldate = {2022-09-23},

journal = {J. Comput. Civ. Eng.},

volume = {36},

number = {3},

pages = {04022006},

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

pubstate = {published},

tppubtype = {article}

}

@article{fujiwara_synchrony_2022,

title = {Synchrony facilitates altruistic decision making for non-human avatars},

author = {Ken Fujiwara and Rens Hoegen and Jonathan Gratch and Norah E. Dunbar},

url = {https://linkinghub.elsevier.com/retrieve/pii/S0747563221004027},

doi = {10.1016/j.chb.2021.107079},

issn = {07475632},

year  = {2022},

date = {2022-03-01},

urldate = {2022-09-28},

journal = {Computers in Human Behavior},

volume = {128},

pages = {107079},

keywords = {DTIC, Virtual Humans},

pubstate = {published},

tppubtype = {article}

}

@article{de_visser_designing_2022,

title = {Designing Man’s New Best Friend: Enhancing Human-Robot Dog Interaction through Dog-Like Framing and Appearance},

author = {Ewart J. Visser and Yigit Topoglu and Shawn Joshi and Frank Krueger and Elizabeth Phillips and Jonathan Gratch and Chad C. Tossell and Hasan Ayaz},

url = {https://www.mdpi.com/1424-8220/22/3/1287},

doi = {10.3390/s22031287},

issn = {1424-8220},

year  = {2022},

date = {2022-02-01},

urldate = {2022-09-28},

journal = {Sensors},

volume = {22},

number = {3},

pages = {1287},

abstract = {To understand how to improve interactions with dog-like robots, we evaluated the importance of “dog-like” framing and physical appearance on interaction, hypothesizing multiple interactive benefits of each. We assessed whether framing Aibo as a puppy (i.e., in need of development) versus simply a robot would result in more positive responses and interactions. We also predicted that adding fur to Aibo would make it appear more dog-like, likable, and interactive. Twenty-nine participants engaged with Aibo in a 2 × 2 (framing × appearance) design by issuing commands to the robot. Aibo and participant behaviors were monitored per second, and evaluated via an analysis of commands issued, an analysis of command blocks (i.e., chains of commands), and using a T-pattern analysis of participant behavior. Participants were more likely to issue the “Come Here” command than other types of commands. When framed as a puppy, participants used Aibo’s dog name more often, praised it more, and exhibited more unique, interactive, and complex behavior with Aibo. Participants exhibited the most smiling and laughing behaviors with Aibo framed as a puppy without fur. Across conditions, after interacting with Aibo, participants felt Aibo was more trustworthy, intelligent, warm, and connected than at their initial meeting. This study shows the benefits of introducing a socially robotic agent with a particular frame and importance on realism (i.e., introducing the robot dog as a puppy) for more interactive engagement.},

keywords = {DTIC, Virtual Humans},

pubstate = {published},

tppubtype = {article}

}

@article{chawla_social_2022,

title = {Social Influence Dialogue Systems: A Survey of Datasets and Models For Social Influence Tasks},

author = {Kushal Chawla and Weiyan Shi and Jingwen Zhang and Gale Lucas and Zhou Yu and Jonathan Gratch},

url = {https://arxiv.org/abs/2210.05664},

doi = {10.48550/ARXIV.2210.05664},

year  = {2022},

date = {2022-01-01},

urldate = {2023-08-22},

abstract = {Dialogue systems capable of social influence such as persuasion, negotiation, and therapy, are essential for extending the use of technology to numerous realistic scenarios. However, existing research primarily focuses on either task-oriented or open-domain scenarios, a categorization that has been inadequate for capturing influence skills systematically. There exists no formal definition or category for dialogue systems with these skills and data-driven efforts in this direction are highly limited. In this work, we formally define and introduce the category of social influence dialogue systems that influence users' cognitive and emotional responses, leading to changes in thoughts, opinions, and behaviors through natural conversations. We present a survey of various tasks, datasets, and methods, compiling the progress across seven diverse domains. We discuss the commonalities and differences between the examined systems, identify limitations, and recommend future directions. This study serves as a comprehensive reference for social influence dialogue systems to inspire more dedicated research and discussion in this emerging area.},

note = {Publisher: arXiv 

Version Number: 2},

keywords = {UARC, Virtual Humans},

pubstate = {published},

tppubtype = {article}

}

@article{hoegen_exploring_2022,

title = {Exploring the Function of Expressions in Negotiation: the DyNego-WOZ Corpus},

author = {Jessie Hoegen and David DeVault and Jonathan Gratch},

doi = {10.1109/TAFFC.2022.3223030},

issn = {1949-3045},

year  = {2022},

date = {2022-01-01},

journal = {IEEE Transactions on Affective Computing},

pages = {1–12},

abstract = {For affective computing to have an impact outside the laboratory, facial expressions must be studied in rich naturalistic situations. We argue negotiations are one such situation as they are ubiquitous in daily life, often evoke strong emotions, and perceived emotion shapes decisions and outcomes. Negotiations are a growing focus in AI research and applications, including agents that negotiate directly with people and attempt to use affective information. We introduce the DyNego-WOZ Corpus, which includes dyadic negotiation between participants and wizard-controlled virtual humans. We demonstrate the value of this corpus to the affective computing community by examining participants' facial expressions in response to a virtual human negotiation partner. We show that people's facial expressions typically co-occur with the end of their partner's speech (suggesting they reflect a reaction to the content of this speech), that these reactions do not correspond to prototypical emotional expressions, and that these reactions can help predict the expresser's subsequent action. We highlight challenges in working with such naturalistic data, including difficulties of expression recognition during speech, and the extreme variability of expressions, both across participants and within a negotiation. Our findings reinforce arguments that facial expressions convey more than emotional state but serve important communicative functions.},

note = {Conference Name: IEEE Transactions on Affective Computing},

keywords = {UARC, Virtual Humans},

pubstate = {published},

tppubtype = {article}

}

@article{schuller_intelligent_2021,

title = {Intelligent Signal Processing for Affective Computing [From the Guest Editors]},

author = {Bjorn W. Schuller and Rosalind Picard and Elisabeth Andre and Jonathan Gratch and Jianhua Tao},

url = {https://ieeexplore.ieee.org/document/9591500/},

doi = {10.1109/MSP.2021.3096415},

issn = {1053-5888, 1558-0792},

year  = {2021},

date = {2021-11-01},

urldate = {2022-09-29},

journal = {IEEE Signal Process. Mag.},

volume = {38},

number = {6},

pages = {9–11},

keywords = {DTIC, Emotions, Virtual Humans},

pubstate = {published},

tppubtype = {article}

}