@article{kellogg_roberts_crespo_2024, title={Automated Image Analysis for Detection of Coccidia in Poultry}, volume={14}, ISSN={["2076-2615"]}, url={https://www.mdpi.com/2076-2615/14/2/212}, DOI={10.3390/ani14020212}, abstractNote={Coccidiosis, caused by the protozoan Eimeria sp., is one of the most common and costly diseases impacting the poultry industry. To establish effective control measures, it is essential to identify these protozoa. Typical methods for identifying and determining the severity of the protozoal infection include intestinal lesion scoring or enumeration of the protozoal oocysts in fecal samples. Standard analysis methods require highly skilled technicians or veterinarians to manually identify and manually enumerate these protozoal parasites. This process is labor intensive, time-consuming, and susceptible to human error. None of the current methods available, including molecular flow cytometry or even digital image analysis, can determine if an oocyst is sporulated or not. Oocysts are not infectious until they sporulate. The goal of this study was to design an automated model using Artificial Intelligence (AI) to expedite the process of enumeration, improve the efficiency and accuracy of the species identification, and determine the ability of the oocysts to infect. To this end, we trained and evaluated computer vision models based on the Mask RCNN neural network architecture. A model was trained to detect and differentiate three species and to determine sporulation for each (totaling six detection groups). This model achieved a mean relative percentage difference (RPD) of 5.64%, representing a slight overcount compared to manual counts, averaging across all groups. The mean RPD for each group individually fell within a range from −33.37% to 52.72%. These results demonstrate that these models were speedy and had high agreement with manual counts, with minimal processing of field-quality samples. These models also could differentiate the sporulation status of the oocysts, providing critical diagnostic information for potential field applications.}, number={2}, journal={ANIMALS}, author={Kellogg, Isaac and Roberts, David L. and Crespo, Rocio}, year={2024}, month={Jan} }
 @article{wu_nichols_foster_martin_dieffenderfer_enomoto_lascelles_russenberger_brenninkmeyer_bozkurt_et al._2023, title={An Exploration of Machine Learning Methods for Gait Analysis of Potential Guide Dogs}, url={https://doi.org/10.1145/3637882.3637883}, DOI={10.1145/3637882.3637883}, abstractNote={Gait analysis is important for guide dog organizations, as ideal guide dogs have a smooth and efficient gait, where they can also easily shift between and maintain various gaits. Gait quality and natural traveling speed are two of the multiple factors important in matching a guide dog to its visually impaired handler. Gait evaluation typically includes subjective visual observation of the dog or objective assessments obtained from special-designed equipment. Guide dog organizations need a method to easily collect and analyze objective data of gait information. In this work, we explored how various machine learning models could learn and analyze gait patterns from inertial measurements data that were collected during two different data collection experiments using a wearable sensor device. We also evaluated how well each machine learning model could generalize behavior patterns from various dogs under different environments. Additionally, we compared how sensor placement locations could affect gait prediction performance by attaching the sensor device to the dog’s neck and back area respectively. The tested machine learning models were able to classify different gaits in the range of 42% to 91% in terms of accuracy, and predict various gait parameters with an error rate ranging from 14% to 29% depending on the setup. Furthermore, we also observed that using behavior data collected from the neck region contains more movement information than the back area. By performing a cross-dataset generalization test on the machine learning models, we found that even with performance drop, the models were able to learn gait-specific behavior patterns that are generalizable for different dogs. Although the results were preliminary, the proposed gait analysis exploration still showed promising potential for studying behavior patterns of candidate guide dogs.}, journal={TENTH INTERNATIONAL CONFERENCE ON ANIMAL-COMPUTER INTERACTION, ACI 2023}, author={Wu, Yifan and Nichols, Colt and Foster, Marc and Martin, Devon and Dieffenderfer, James and Enomoto, Masataka and Lascelles, B. Duncan X. and Russenberger, Jane and Brenninkmeyer, Gerald and Bozkurt, Alper and et al.}, year={2023} }
 @article{menzies_johnson_roberts_alvarez_2023, title={The Engineering Mindset Is an Ethical Mindset (We Just Don't Teach It That Way ... Yet)}, volume={40}, ISSN={["1937-4194"]}, url={https://doi.org/10.1109/MS.2022.3227597}, DOI={10.1109/MS.2022.3227597}, abstractNote={Can achieve an ethical engineering mindset without detracting from the core technical topics of CS subjects? Some doubt that this is possible. Lately we have been involved in too many discussions where participants were worried about how to teach ethics to SE/CS students. The problem, we heard, was too hard and too complex. In this short note, we beg to differ. Ethics is a well-studied issue. Philosophers have studied and taught ethics and civics for generations. Similarly, computer scientists and software engineers have assembled an extensive set of skills and resources which are relevant to an ethical education. Using those resources, this paper offers a proof-by-example of a CS class syllabus that (a) enables an ethical engineering mindset while (b) not detracting from core technical topics.}, number={2}, journal={IEEE SOFTWARE}, author={Menzies, Tim and Johnson, Brittany L. and Roberts, David and Alvarez, Lauren}, year={2023}, pages={103–110} }
 @article{martin_roberts_bozkurt_2023, title={Toward In-the-Field Canine Manifold Learning: Data Fusion for Evaluation of Potential Guide Dogs}, DOI={10.1145/3637882.3637898}, journal={TENTH INTERNATIONAL CONFERENCE ON ANIMAL-COMPUTER INTERACTION, ACI 2023}, author={Martin, Devon and Roberts, David and Bozkurt, Alper}, year={2023} }
 @article{holder_nichols_summers_roberts_bozkurt_2023, title={Towards a Multimodal Synchronized System for Quantifying Psychophysiological States in Canine Assisted Interactions}, DOI={10.1145/3637882.3637886}, journal={TENTH INTERNATIONAL CONFERENCE ON ANIMAL-COMPUTER INTERACTION, ACI 2023}, author={Holder, Timothy and Nichols, Colt and Summers, Emily and Roberts, David L. and Bozkurt, Alper}, year={2023} }
 @article{martin_holder_nichols_park_roberts_bozkurt_2022, title={Comparing Accelerometry and Depth Sensing-Based Computer Vision for Canine Tail Wagging Interpretation}, DOI={10.1145/3565995.3566025}, abstractNote={This paper presents a preliminary effort to evaluate alternative sensing modalities for automated, high-resolution tracking of dog tail position and movement as a behavioral communication tool. We compare two different methods: (1) inertial measurement devices placed on dog outfits, and (2) remotely positioned cameras supported with custom vision-based tail wag detection algorithms. The small size and non-invasiveness of the inertial sensors and the non-contact and remote nature of the camera system both promote subject comfort and continuous signal acquisition while not affecting the mechanics of dog tail movement. The preliminary findings support that the higher-resolution and continuous interpretations on the dog tail movements and positions can pave the way for assessing their emotional states and designing more appropriate training and play environments.}, journal={NINTH INTERNATIONAL CONFERENCE ON ANIMAL-COMPUTER INTERACTION, ACI 2022}, author={Martin, Devon and Holder, Timothy and Nichols, Colt and Park, Jeremy and Roberts, David and Bozkurt, Alper}, year={2022} }
 @article{holder_rahman_summers_roberts_wong_bozkurt_2022, title={Contact-Free Simultaneous Sensing of Human Heart Rate and Canine Breathing Rate for Animal Assisted Interactions}, DOI={10.1145/3565995.3566039}, abstractNote={Animal Assisted Interventions (AAIs) involve pleasant interactions between humans and animals and can potentially benefit both types of participants. Research in this field may help to uncover universal insights about cross-species bonding, dynamic affect detection, and the influence of environmental factors on dyadic interactions. However, experiments evaluating these outcomes are limited to methodologies that are qualitative, subjective, and cumbersome due to the ergonomic challenges related to attaching sensors to the body. Current approaches in AAIs also face challenges when translating beyond controlled clinical environments or research contexts. These also often neglect the measurements from the animal throughout the interaction. Here, we present our preliminary effort toward a contact-free approach to facilitate AAI assessment via the physiological sensing of humans and canines using consumer-grade cameras. This initial effort focuses on verifying the technological feasibility of remotely sensing the heart rate signal of the human subject and the breathing rate signal of the dog subject while they are interacting. Small amounts of motion such as patting and involuntary body shaking or movement can be tolerated with our custom designed vision-based algorithms. The experimental results show that the physiological measurements obtained by our algorithms were consistent with those provided by the standard reference devices. With further validation and expansion to other physiological parameters, the presented approach offers great promise for many scenarios from the AAI research space to veterinary, surgical, and clinical applications.}, journal={NINTH INTERNATIONAL CONFERENCE ON ANIMAL-COMPUTER INTERACTION, ACI 2022}, author={Holder, Timothy and Rahman, Mushfiqur and Summers, Emily and Roberts, David and Wong, Chau-Wai and Bozkurt, Alper}, year={2022} }
 @article{wang_foster_bozkurt_roberts_2022, title={Motion-Resilient ECG Signal Reconstruction from a Wearable IMU through Attention Mechanism and Contrastive Learning}, url={https://doi.org/10.1145/3565995.3566037}, DOI={10.1145/3565995.3566037}, abstractNote={Wearable electrocardiogram (ECG) sensors can detect dogs’ heartbeat signals and have proven useful in monitoring dogs’ welfare and predicting temperament scores in structured evaluations of potential guide dog puppies. Despite advances in the ergonomics, performance, and usability of ECG sensor technologies specifically designed for dogs, deploying those systems in the real world imposes challenges such as training human operators to ensure electrodes’ proper contact with the skin and, especially in the case of puppies, socialization to achieve comfort and reduce behavioral inhibition. Seismocardiogram signal is an alternate modality for heartbeat signals and is acquired using the Inertial Measurement Unit (IMU), which is commercially available, widely deployed, and does not require skin-contact. However, the extracted signals from IMU are subject to heavy influences from motion and other noise sources. In this paper, we present a method that enables extracting the similar physiological parameters ECG provides using easier-to-deploy IMU sensors. We propose and evaluate a machine learning framework that reconstructs ECG signals from IMU signals even under moderate to heavy movements. Our study investigated two artificial neural network architectures to overcome severe noise artifacts in the IMU signal resulting from dogs’ movements and environmental factors. The first architecture combines the attention mechanism and convolution layers to extract important features from the temporal IMU input. The second architecture adapts contrastive representation learning to the regression problem and learns a more effective embedding for the ECG reconstruction. The qualitative inspection and quantitative analysis based on F1 scores of the R-peak alignment demonstrate the effectiveness of the two proposed models in removing motion noises and reconstructing realistic ECG signals, achieving an F1 score of 0.72 in the best case compared to 0.29 from the baseline.}, journal={NINTH INTERNATIONAL CONFERENCE ON ANIMAL-COMPUTER INTERACTION, ACI 2022}, author={Wang, Jianxun and Foster, Marc and Bozkurt, Alper and Roberts, David L.}, year={2022} }
 @article{foster_wu_roberts_bozkurt_2022, title={Preliminary Evaluation of a System with On-Body and Aerial Sensors for Monitoring Working Dogs}, volume={22}, ISSN={["1424-8220"]}, url={https://doi.org/10.3390/s22197631}, DOI={10.3390/s22197631}, abstractNote={This paper presents a system for behavioral, environmental, and physiological monitoring of working dogs using on-body and aerial sensors. The proof of concept study presented here includes two trained dogs performing nine scent detection tasks in an uncontrolled environment encompassing approximately two acres. The dogs were outfitted with a custom designed wearable harness to monitor their heart rate, activity levels and skin temperature. We utilized a commercially available micro-air vehicle to perform aerial sensing by tracking the terrain and movement of the dog in the outdoor space. The dogs were free to explore the space working at maximal speeds to complete a scent-based search-and-retrieval task. Throughout the experiment, the harness data was transferred to a base station via Wi-Fi in real-time. In this work, we also focused on testing the performance of a custom 3D electrode with application specific ergonomic improvements and adaptive filter processing techniques to recover as much electrocardiography data as possible during high intensity motion activity. We were able to recover and use 84% of the collected data where we observed a trend of heart rate generally increasing immediately after successful target localization. For tracking the dogs in the aerial video footage, we applied a state-of-the-art deep learning algorithm designed for online object tracking. Both qualitative and quantitative tracking results are very promising. This study presents an initial effort towards deployment of on-body and aerial sensors to monitor the working dogs and their environments during scent detection and search and rescue tasks in order to ensure their welfare, enable novel dog-machine interfaces, and allow for higher success rate of remote and automated task performance.}, number={19}, journal={SENSORS}, author={Foster, Marc and Wu, Tianfu and Roberts, David L. and Bozkurt, Alper}, year={2022}, month={Oct} }
 @article{wu_holder_foster_williams_enomoto_lascelles_bozkurt_roberts_2022, title={Spatial and Temporal Analytic Pipeline for Evaluation of Potential Guide Dogs Using Location and Behavior Data}, url={https://doi.org/10.1145/3565995.3566033}, DOI={10.1145/3565995.3566033}, abstractNote={Training guide dogs for visually-impaired people is a resource-consuming task for guide dog schools. This task is further complicated by a dearth of capabilities to objectively measure and analyze candidate guide dogs’ temperaments as they are placed with volunteer raisers away from guide dog schools for months during the raising process. In this work, we demonstrate a preliminary data analysis workflow that is able to provide detailed information about candidate guide dogs’ day to day physical exercise levels and gait activities using objective environmental and behavioral data collected from a wearable collar-based Internet of Things device. We trained and tested machine learning models to analyze different gait types including walking, pacing, trotting and mixture of walk and trot. By analyzing data both spatially and temporally, a location and behavior summary for candidate dogs is generated to provide insight for guide dog training experts, so that they can more accurately and comprehensively evaluate the future success of the candidate. The preliminary analysis revealed movement patterns for different location types which reflected the behaviors of candidate guide dogs.}, journal={NINTH INTERNATIONAL CONFERENCE ON ANIMAL-COMPUTER INTERACTION, ACI 2022}, author={Wu, Yifan and Holder, Timothy and Foster, Marc and Williams, Evan and Enomoto, Masataka and Lascelles, B. Duncan X. and Bozkurt, Alper and Roberts, David L.}, year={2022} }
 @article{jara_crespo_roberts_chapman_banda_machado_2021, title={Development of a Dissemination Platform for Spatiotemporal and Phylogenetic Analysis of Avian Infectious Bronchitis Virus}, volume={8}, ISSN={["2297-1769"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85105984090&partnerID=MN8TOARS}, DOI={10.3389/fvets.2021.624233}, abstractNote={Infecting large portions of the global poultry populations, the avian infectious bronchitis virus (IBV) remains a major economic burden in North America. With more than 30 serotypes globally distributed, Arkansas, Connecticut, Delaware, Georgia, and Massachusetts are among the most predominant serotypes in the United States. Even though vaccination is widely used, the high mutation rate exhibited by IBV is continuously triggering the emergence of new viral strains and hindering control and prevention measures. For that reason, targeted strategies based on constantly updated information on the IBV circulation are necessary. Here, we sampled IBV-infected farms from one US state and collected and analyzed 65 genetic sequences coming from three different lineages along with the immunization information of each sampled farm. Phylodynamic analyses showed that IBV dispersal velocity was 12.3 km/year. The majority of IBV infections appeared to have derived from the introduction of the Arkansas DPI serotype, and the Arkansas DPI and Georgia 13 were the predominant serotypes. When analyzed against IBV sequences collected across the United States and deposited in the GenBank database, the most likely viral origin of our sequences was from the states of Alabama, Georgia, and Delaware. Information about vaccination showed that the MILDVAC-MASS+ARK vaccine was applied on 26% of the farms. Using a publicly accessible open-source tool for real-time interactive tracking of pathogen spread and evolution, we analyzed the spatiotemporal spread of IBV and developed an online reporting dashboard. Overall, our work demonstrates how the combination of genetic and spatial information could be used to track the spread and evolution of poultry diseases, providing timely information to the industry. Our results could allow producers and veterinarians to monitor in near-real time the current IBV strain circulating, making it more informative, for example, in vaccination-related decisions.}, journal={FRONTIERS IN VETERINARY SCIENCE}, author={Jara, Manuel and Crespo, Rocio and Roberts, David L. and Chapman, Ashlyn and Banda, Alejandro and Machado, Gustavo}, year={2021}, month={May} }
 @article{holder_gruen_roberts_somers_bozkurt_2020, title={A Systematic Literature Review of
Animal-Assisted Interventions in Oncology
(Part I): Methods and Results}, volume={19}, ISSN={["1552-695X"]}, DOI={10.1177/1534735420943278}, abstractNote={ Animal-assisted interventions (AAIs) use human-animal interactions to positive effect in various contexts including cancer care. As the first installment of a 2-part series, this systematic literature review focuses on the research methods and quantitative results of AAI studies in oncology. We find methodological consistency in the use of canines as therapy animals, in the types of high-risk patients excluded from studies, and in the infection precautions taken with therapy animals throughout cancer wards. The investigated patient endpoints are not significantly affected by AAI, with the exceptions of improvements in oxygen consumption, quality of life, depression, mood, and satisfaction with therapy. The AAI field in oncology has progressed significantly since its inception and has great potential to positively affect future patient outcomes. To advance the field, future research should consistently improve the methodological design of studies, report data more completely, and focus more on the therapy animal’s well-being. }, journal={Integrative Cancer Therapies}, author={Holder, T. and Gruen, M. and Roberts, D. and Somers, T. and Bozkurt, A.}, year={2020}, month={Aug}, pages={1–19} }
 @misc{holder_gruen_roberts_somers_bozkurt_2020, title={A Systematic Literature Review of Animal-Assisted Interventions in Oncology (Part II): Theoretical Mechanisms and Frameworks}, volume={19}, ISSN={["1552-695X"]}, DOI={10.1177/1534735420943269}, abstractNote={Animal-assisted interventions (AAIs) can improve patients’ quality of life as complementary medical treatments. Part I of this 2-paper systematic review focused on the methods and results of cancer-related AAIs; Part II discusses the theories of the field’s investigators. Researchers cite animal personality, physical touch, physical movement, distraction, and increased human interaction as sources of observed positive outcomes. These mechanisms then group under theoretical frameworks such as the social support hypothesis or the human-animal bond concept to fully explain AAI in oncology. The cognitive activation theory of stress, the science of unitary human beings, and the self-object hypothesis are additional frameworks mentioned by some researchers. We also discuss concepts of neurobiological transduction connecting mechanisms to AAI benefits. Future researchers should base study design on theories with testable hypotheses and use consistent terminology to report results. This review aids progress toward a unified theoretical framework and toward more holistic cancer treatments.}, journal={INTEGRATIVE CANCER THERAPIES}, author={Holder, Timothy R. N. and Gruen, Margaret E. and Roberts, David L. and Somers, Tamara and Bozkurt, Alper}, year={2020}, month={Jul} }
 @article{foster_brugarolas_walker_mealin_cleghern_yuschak_clark_adin_russenberger_gruen_et al._2020, title={Preliminary Evaluation of a Wearable Sensor System for Heart Rate Assessment in Guide Dog Puppies}, volume={20}, ISSN={["1558-1748"]}, url={https://doi.org/10.1109/JSEN.2020.2986159}, DOI={10.1109/JSEN.2020.2986159}, abstractNote={This paper details the development of a novel wireless heart rate sensing system for puppies in training as guide dogs. The system includes a harness with on-board electrocardiography (ECG) front-end circuit, inertial measurement unit and a micro-computer with wireless capability where the major research focus of this paper was on the ergonomic design and evaluation of the system on puppies. The first phase of our evaluation was performed on a Labrador Retriever between 12 to 26 weeks in age as a pilot study. The longitudinal weekly data collected revealed the expected trend of a decreasing average heart rate and increased heart rate variability as the age increased. In the second phase, we improved the system ergonomics for a larger scale deployment in a guide dog school (Guiding Eyes for the Blind (Guiding Eyes)) on seventy 7.5-week-old puppies (heart rate coverage average of 86.7%). The acquired ECG based heart rate data was used to predict the performance of puppies in Guiding Eyes’s temperament test. We used the data as an input to a machine learning model which predicted two Behavior Checklist (BCL) scores as determined by expert Guiding Eyes puppy evaluators with an accuracy above 90%.}, number={16}, journal={IEEE SENSORS JOURNAL}, publisher={Institute of Electrical and Electronics Engineers (IEEE)}, author={Foster, Marc and Brugarolas, Rita and Walker, Katherine and Mealin, Sean and Cleghern, Zach and Yuschak, Sherrie and Clark, Julia Condit and Adin, Darcy and Russenberger, Jane and Gruen, Margaret and et al.}, year={2020}, pages={9449–9459} }
 @article{brugarolas_yuschak_adin_roberts_sherman_bozkurt_2019, title={Simultaneous Monitoring of Canine Heart Rate and Respiratory Patterns During Scent Detection Tasks}, volume={19}, ISSN={["1558-1748"]}, DOI={10.1109/JSEN.2018.2883066}, abstractNote={Man-made technological odor detection systems continue to improve but still cannot match the tracking efficiency, mobility, and selectivity in the presence of interfering odors achieved by detector dogs. The reliability of dogs as olfactory detectors does not depend solely on their performance but also on the handler’s skill in interpreting the behavior of the dog that signals the detection of the target odor. We present our efforts on a wireless wearable system combining electrocardiogram (ECG) and an electronic stethoscope for direct monitoring of cardiopulmonary events in dogs toward enabling cybernetic dog–machine interfaces. This is, to our knowledge, the first cyber-physical attempt to simultaneously record heart rate, heart rate variability, and continuous auscultation of respiratory behavior in a wearable form factor during scent-detection tasks. In this paper, we present: 1) a method to automate the detection of sniffing episodes based on power spectral density of the respiratory sounds; 2) proof-of-concept extraction and quantification of the ECG and respiratory sounds features that would enable the discovery of physiological patterns associated to scent-detection tasks; and 3) proof-of-concept correlation of such patterns with the presence/absence of target odors. These contributions pave the way for a novel real-time cybernetic olfactory detection monitoring system to provide decision support for handlers in the field in addition to enabling future computer-sniffing dog interfaces.}, number={4}, journal={IEEE SENSORS JOURNAL}, author={Brugarolas, Rita and Yuschak, Sherrie and Adin, Darcy and Roberts, David L. and Sherman, Barbara L. and Bozkurt, Alper}, year={2019}, month={Feb}, pages={1454–1462} }
 @article{majikes_brugarolas_winters_yuschak_mealin_walker_yang_sherman_bozkurt_roberts_2017, title={Balancing noise sensitivity, response latency, and posture accuracy for a computer-assisted canine posture training system}, volume={98}, ISSN={["1095-9300"]}, DOI={10.1016/j.ijhcs.2016.04.010}, abstractNote={This paper describes a canine posture detection system composed of wearable sensors and instrumented devices that detect the postures sit, stand, and eat. The system consists of a customized harness outfitted with wearable Inertial Measurement Units (IMUs) and a base station for processing IMU data to classify canine postures. Research in operant conditioning, the science of behavior change, indicates that successful animal training requires consistent and accurate feedback on behavior. Properly designed computer systems excel at timeliness and accuracy, which are two characteristics most amateur trainers struggle with and professionals strive for. Therefore, in addition to the system being ergonomically designed to ensure the dog׳s comfort and well-being, it is engineered to provide posture detection with timing and accuracy on par with a professional trainer. We contend that providing a system with these characteristics will one day aid dogs in learning from humans by overcoming poor or ineffective timing during training. We present the initial steps in the development and validation of a computer-assisted training system designed to work outside of laboratory environments. The main contributions of this work are (a) to explore the trade-off between low-latency responses to changes in time-series IMU data representative of posture changes while maintaining accuracy and timing similar to a professional trainer, and (b) to provide a model for future ACI technologies by documenting the user-centered approach we followed to create a computer-assisted training system that met the criteria identified in (a). Accordingly, in addition to describing our system, we present the results of three experiments to characterize the performance of the system at capturing sit postures of dogs and providing timely reinforcement. These trade-offs are illustrated through the comparison of two algorithms. The first is Random Forest classification and the second is an algorithm which uses a Variance-based Threshold for classification of postures. Results indicate that with proper parameter tuning, our system can successfully capture and reinforce postures to provide computer-assisted training of dogs.}, journal={INTERNATIONAL JOURNAL OF HUMAN-COMPUTER STUDIES}, author={Majikes, John and Brugarolas, Rita and Winters, Michael and Yuschak, Sherrie and Mealin, Sean and Walker, Katherine and Yang, Pu and Sherman, Barbara and Bozkurt, Alper and Roberts, David L.}, year={2017}, month={Feb}, pages={179–195} }
 @article{dominguez_goodwin_roberts_st amant_2017, title={Human Subtlety Proofs: Using Computer Games to Model Cognitive Processes for Cybersecurity}, volume={33}, ISSN={["1532-7590"]}, DOI={10.1080/10447318.2016.1232229}, abstractNote={ABSTRACT This article describes an emerging direction in the intersection between human–computer interaction and cognitive science: the use of cognitive models to give insight into the challenges of cybersecurity (cyber-SA). The article gives a brief overview of work in different areas of cyber-SA where cognitive modeling research plays a role, with regard to direct interaction between end users and computer systems and with regard to the needs of security analysts working behind the scenes. The problem of distinguishing between human users and automated agents (bots) interacting with computer systems is introduced, as well as ongoing efforts toward building Human Subtlety Proofs (HSPs), persistent and unobtrusive windows into human cognition with direct application to cyber-SA. Two computer games are described, proxies to illustrate different ways in which cognitive modeling can potentially contribute to the development of HSPs and similar cyber-SA applications.}, number={1}, journal={INTERNATIONAL JOURNAL OF HUMAN-COMPUTER INTERACTION}, author={Dominguez, Ignacio X. and Goodwin, Prairie Rose and Roberts, David L. and St Amant, Robert}, year={2017}, pages={44–54} }
 @inproceedings{cleghern_lahiri_ozaltin_roberts_2017, title={Predicting future states in dota 2 using value-split models of time series attribute data}, booktitle={Proceedings of the 12th International Conference on the Foundations of Digital Games (FDG'17)}, author={Cleghern, Z. and Lahiri, S. and Ozaltin, O. and Roberts, D. L.}, year={2017} }
 @inbook{majikes_yuschak_walker_brugarolas_mealin_foster_bozkurt_sherman_roberts_2017, title={Stimulus Control for Semi-autonomous Computer Canine-Training}, ISBN={9783319635361 9783319635378}, ISSN={0302-9743 1611-3349}, url={http://dx.doi.org/10.1007/978-3-319-63537-8_24}, DOI={10.1007/978-3-319-63537-8_24}, abstractNote={For thousands of years, humans have domesticated and trained dogs to perform tasks for them. Humans have developed areas of study, such as Applied Behavior Analysis, which aim to improve the training process. We introduce a semi-autonomous, canine-training system by combining existing research in Applied Behavior Analysis with computer systems consisting of hardware, software, audio, and visual components. These components comprise a biohybrid system capable of autonomously training a dog to perform a specific behavior on command. In this paper we further our previous computer canine-training system by the application of stimulus control over a newly-acquired, free operant behavior. This system uses light and sound as a discriminative stimulus for the behavior of a dog pushing a button with its nose. Indications of simple stimulus control of this behavior were achieved. Our pilot of this system indicates canine learning comparable to that from a professional dog trainer.}, booktitle={Biomimetic and Biohybrid Systems}, publisher={Springer International Publishing}, author={Majikes, John J. and Yuschak, Sherrie and Walker, Katherine and Brugarolas, Rita and Mealin, Sean and Foster, Marc and Bozkurt, Alper and Sherman, Barbara and Roberts, David L.}, year={2017}, pages={279–290} }
 @article{loftin_peng_macglashan_littman_taylor_huang_roberts_2016, title={Learning behaviors via human-delivered discrete feedback: modeling implicit feedback strategies to speed up learning}, volume={30}, ISSN={["1573-7454"]}, DOI={10.1007/s10458-015-9283-7}, number={1}, journal={AUTONOMOUS AGENTS AND MULTI-AGENT SYSTEMS}, author={Loftin, Robert and Peng, Bei and MacGlashan, James and Littman, Michael L. and Taylor, Matthew E. and Huang, Jeff and Roberts, David L.}, year={2016}, month={Jan}, pages={30–59} }
 @article{mealin_dominguez_roberts_2016, title={Semi-supervised Classification of Static Canine Postures Using the Microsoft Kinect}, DOI={10.1145/2995257.3012024}, abstractNote={3D sensing hardware, such as the Microsoft Kinect, allows new interaction paradigms that would be difficult to accomplish with traditional RGB cameras alone. One basic step in realizing these new methods of animal-computer interaction is posture and behavior detection and classification. In this paper, we present a system capable of identifying static postures for canines that does not rely on hand-labeled data at any point during the process. We create a model of the canine based on measurements automatically obtained in from the first few captured frames, reducing the burden on users. We also present a preliminary evaluation of the system with five dogs, which shows that the system can identify the "standing," "sitting," and "lying" postures with approximately 70%, 69%, and 94% accuracy, respectively.}, journal={PROCEEDINGS OF THE THIRD INTERNATIONAL CONFERENCE ON ANIMAL-COMPUTER INTERACTION, ACI 2016}, author={Mealin, Sean and Dominguez, Ignacio X. and Roberts, David L.}, year={2016} }
 @inproceedings{majikes_mealin_rita_walker_yuschak_sherman_bozkurt_roberts_2016, title={Smart connected canines: IoT design considerations for the lab, home, and mission-critical environments (invited paper)}, DOI={10.1109/sarnof.2016.7846739}, abstractNote={The canine-human relationship continues to grow as dogs become an increasingly critical part of our society. As reliance on dogs has increased from simple companionship, to service dogs, urban security, and national defense, the opportunities for enhanced communications between the working canine and their handler increase. Wireless sensor networks and the Internet of Things (IoT) can extend traditional canine-human communication to integrate canines into the cyber-enabled world. This is what we call the Smart Connected Canine (SCC). Canine-computer interaction is sufficiently different from human-computer interaction so as to present some challenging research and design problems. There are physical and performance limits to what a dog will naturally tolerate. There are communications requirements for monitoring dogs, monitoring the environment, and for canine-human communications. Depending on the working environment there are different performance, security, and ergonomic considerations. This paper summarizes three example canine-human systems we presented earlier along with their Ion data characteristics and design criteria in order to explore how smart connected canines can improve our lives, the future of smart connected canines, and the requirements on IoT technologies to facilitate this future.}, booktitle={2016 ieee 37th sarnoff symposium}, author={Majikes, J. J. and Mealin, S. and Rita, B. and Walker, K. and Yuschak, S. and Sherman, B. and Bozkurt, A. and Roberts, D. L.}, year={2016}, pages={118–123} }
 @article{dominguez_cardona-rivera_vance_roberts_2016, title={The Mimesis Effect: The Effect of Roles on Player Choice in Interactive Narrative Role-Playing Games}, DOI={10.1145/2858036.2858141}, abstractNote={We present a study that investigates the heretofore unexplored relationship between a player's sense of her narrative role in an interactive narrative role-playing game and the options she selects when faced with choice structures during gameplay. By manipulating a player's knowledge over her role, and examining in-game options she preferred in choice structures, we discovered what we term the Mimesis Effect: when players were explicitly given a role, we found a significant relationship between their role and their in-game actions; participants role-play even if not instructed to, exhibiting a preference for actions consistent with their role. Further, when players were not explicitly given a role, participants still role-played -- they were consistent with an implicit role -- but did not agree on which role to implicitly be consistent with. We discuss our findings and broader implications of our work to both game development and games research.}, journal={34TH ANNUAL CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS, CHI 2016}, author={Dominguez, Ignacio X. and Cardona-Rivera, Rogelio E. and Vance, James K. and Roberts, David L.}, year={2016}, pages={3438–3449} }
 @inbook{mealin_howell_roberts_2016, title={Towards Unsupervised Canine Posture Classification via Depth Shadow Detection and Infrared Reconstruction for Improved Image Segmentation Accuracy}, ISBN={9783319424163 9783319424170}, ISSN={0302-9743 1611-3349}, url={http://dx.doi.org/10.1007/978-3-319-42417-0_15}, DOI={10.1007/978-3-319-42417-0_15}, abstractNote={Hardware capable of 3D sensing, such as the Microsoft Kinect, has opened up new possibilities for low-cost computer vision applications. In this paper, we take the first steps towards unsupervised canine posture classification by presenting an algorithm to perform canine-background segmentation, using depth shadows and infrared data for increased accuracy. We report on two experiments to show that the algorithm can operate at various distances and heights, and examine how that effects its accuracy. We also perform a third experiment to show that the output of the algorithm can be used for k-means clustering, resulting in accurate clusters 83 % of the time without any preprocessing and when the segmentation algorithm is at least 90 % accurate.}, booktitle={Biomimetic and Biohybrid Systems}, publisher={Springer International Publishing}, author={Mealin, Sean and Howell, Steven and Roberts, David L.}, year={2016}, pages={155–166} }
 @inproceedings{brugarolas_agcayazi_yuschak_roberts_sherman_bozkurt_2016, title={Towards a wearable system for continuous monitoring of sniffing and panting in dogs}, DOI={10.1109/bsn.2016.7516276}, abstractNote={Although numerous advances have been made in instrumental odor detection systems, these still cannot match the efficient sampling, odor discrimination, agile mobility and the olfactory acuity of odor detection dogs. A limiting step in using dogs to detect odors is the subjectivity of the translation of odor information processed by the dog to its handler. We present our preliminary efforts towards a wireless wearable system for continuous auscultation of respiratory behavior by recording internal sounds at the neck and chest by means of a commercially available electronic stethoscope to provide objective decision support for handlers. We have identified discrete features of sniffing and panting in the time domain and utilize event duration, event rate, event mean energy, and the number of consecutive events in a row to build a decision tree classifier. Since feature extraction requires segmentation of individual sniffing and panting events, we developed an adaptive method using short-time energy contour and an adaptive threshold. The performance of the system was evaluated on recordings from a Greyhound and a Labrador Retriever and achieved high classification accuracies.}, booktitle={International conference on wearable and implantable body sensor}, author={Brugarolas, R. and Agcayazi, T. and Yuschak, S. and Roberts, D. L. and Sherman, B. L. and Bozkurt, A.}, year={2016}, pages={292–295} }
 @inproceedings{mealin_howell_roberts_2016, title={Towards unsupervised canine posture classification via depth shadow detection and infrared reconstruction for improved image segmentation accuracy}, volume={9793}, booktitle={Biomimetic and biohybrid systems, living machines 2016}, author={Mealin, S. and Howell, S. and Roberts, D. L.}, year={2016}, pages={155–166} }
 @article{brugarolas_latif_dieffenderfer_walker_yuschak_sherman_roberts_bozkurt_2016, title={Wearable Heart Rate Sensor Systems for Wireless Canine Health Monitoring}, volume={16}, ISSN={["1558-1748"]}, DOI={10.1109/jsen.2015.2485210}, abstractNote={There is an increasing interest from dog handlers and veterinarians in an ability to continuously monitor dogs' vital signs (heart rate, heart rate variability, and respiratory rate) outside laboratory environments, with the aim of identifying physiological correlations to stress, distress, excitement, and other emotional states. We present a non-invasive wearable sensor system combining electrocardiogram (ECG), photoplethysmogram (PPG), and inertial measurement units (IMU) to remotely and continuously monitor the vital signs of dogs. To overcome the limitations imposed by the efficiently insulated skin and dense hair layers of dogs, we investigated the use of various styles of ECG electrodes and the enhancements of these by conductive polymer coatings. We also studied the incorporation of light guides and optical fibers for an efficient optical coupling of PPG sensors to the skin. Combined with our parallel efforts to use IMUs to identify dog behaviors, these physiological sensors will contribute to a canine-body area network to wirelessly and continuously collect data during canine activities with a long-term goal of effectively capturing and interpreting dogs' behavioral responses to environmental stimuli that may yield measurable benefits to handlers' interactions with their dogs.}, number={10}, journal={IEEE SENSORS JOURNAL}, author={Brugarolas, Rita and Latif, Tahmid and Dieffenderfer, James and Walker, Katherine and Yuschak, Sherrie and Sherman, Barbara L. and Roberts, David L. and Bozkurt, Alper}, year={2016}, month={May}, pages={3454–3464} }
 @article{harrison_roberts_2015, title={An Analytic and Psychometric Evaluation of Dynamic Game Adaption for Increasing Session-Level Retention in Casual Games}, volume={7}, ISSN={["1943-0698"]}, DOI={10.1109/tciaig.2015.2410757}, abstractNote={This paper shows how game analytics can be used to dynamically adapt casual game environments in order to increase session-level retention. Our technique involves using game analytics to create an abstracted game analytic space to make the problem tractable. We then model player retention in this space and use these models to make guided changes to game analytics in order to bring about a targeted distribution of game states that will, in turn, influence player behavior. Experiments performed showed that the adaptive versions of two different casual games, Scrabblesque and Sidequest: The Game, were able to better fit a target distribution of game states while also significantly reducing the quitting rate compared to the nonadaptive version of the games. We showed that these gains were not coming at the cost of player experience by performing a psychometric evaluation in which we measured player intrinsic motivation and engagement with the game environments. In both cases, we showed that players playing the adaptive version of the games reported higher intrinsic motivation and engagement scores than players playing the nonadaptive version of the games.}, number={3}, journal={IEEE TRANSACTIONS ON COMPUTATIONAL INTELLIGENCE AND AI IN GAMES}, author={Harrison, Brent and Roberts, David L.}, year={2015}, month={Sep}, pages={207–219} }
 @article{winters_brugarolas_majikes_mealin_yuschak_sherman_bozkurt_roberts_2015, title={Knowledge Engineering for Unsupervised Canine Posture Detection from IMU Data}, DOI={10.1145/2832932.2837015}, abstractNote={Training animals is a process that requires a significant investment of time and energy on the part of the trainer. One of the most basic training tasks is to train dogs to perform postures on cue. While it might be easy for a human trainer to see when an animal has performed the desired posture, it is much more difficult for a computer to determine this. Most work in this area uses accelerometer and/or gyroscopic data to produce data from an animal's current state, but this has limitations. Take for example a normal standing posture. From an accelerometer's perspective, it closely resembles the "laying down" posture, but the posture can look very different if the animal is standing still, versus walking, versus running, and might look completely different from a "standing on incline" posture. A human trainer can instantly tell the difference between these postures and behaviors, but the process is much more difficult for a computer. This paper demonstrates several algorithms for recognizing canine postures, as well as a system for building a computational model of a canine's potential postures, based solely on skeletal measurements. Existing techniques use labeled data, which can be difficult to acquire. We contribute a new technique for unsupervised posture detection, and compare the supervised technique to our new, unsupervised technique. Results indicate that the supervised technique performs with a mean 82.06% accuracy, while our unsupervised approach achieves a mean 74.25% accuracy, indicating that in some cases, our new unsupervised technique is capable of achieving comparable performance.}, journal={12TH ADVANCES IN COMPUTER ENTERTAINMENT TECHNOLOGY CONFERENCE (ACE15)}, author={Winters, Michael and Brugarolas, Rita and Majikes, John and Mealin, Sean and Yuschak, Sherrie and Sherman, Barbara L. and Bozkurt, Alper and Roberts, David}, year={2015} }
 @article{mealin_winters_dominguez_marrero-garcia_bozkurt_sherman_roberts_2015, title={Towards the Non-Visual Monitoring of Canine Physiology in Real-Time by Blind Handlers}, DOI={10.1145/2832932.2837018}, abstractNote={One of the challenges to working with canines is that whereas humans are primarily vocal communicators, canines are primarily postural and behavioral communicators. It can take years to gain some level of proficiency at reading canine body language, even under the best of circumstances. In the case of guide dogs and visually-impaired handlers, this task is even more difficult. Luckily, new technology designed to help monitor canines may prove useful in helping handlers, especially those with visual impairments, to better understand and interpret what their working partners are feeling or saying. In prior work a light-weight, wearable, wireless physiological monitoring system was shown to be accurate for measuring canines' heart and respiratory rates [6]. In this paper, we consider the complementary problem of communicating physiological information to handlers. We introduce two non-visual interfaces for monitoring a canine's heart and respiratory rates, an audio interface and a vibrotactile interface. We also present the results of two initial studies to evaluate the efficacy of the interfaces. In the first study we found that many participants were more confident in detecting changes in heart and respiratory rate using the audio interface, however most of the time they were just as accurate with the vibrotactile interface with only a slight increase in detection latency.}, journal={12TH ADVANCES IN COMPUTER ENTERTAINMENT TECHNOLOGY CONFERENCE (ACE15)}, author={Mealin, Sean and Winters, Mike and Dominguez, Ignacio X. and Marrero-Garcia, Michelle and Bozkurt, Alper and Sherman, Barbara L. and Roberts, David L.}, year={2015} }
 @article{ware_young_harrison_roberts_2014, title={A Computational Model of Plan-Based Narrative Conflict at the Fabula Level}, volume={6}, ISSN={1943-068X 1943-0698}, url={http://dx.doi.org/10.1109/tciaig.2013.2277051}, DOI={10.1109/tciaig.2013.2277051}, abstractNote={Conflict is an essential element of interesting stories. In this paper, we operationalize a narratological definition of conflict and extend established narrative planning techniques to incorporate this definition. The conflict partial order causal link planning algorithm (CPOCL) allows narrative conflict to arise in a plan while maintaining causal soundness and character believability. We also define seven dimensions of conflict in terms of this algorithm's knowledge representation. The first three-participants, reason, and duration-are discrete values which answer the “who?” “why?” and “when?” questions, respectively. The last four-balance, directness, stakes, and resolution-are continuous values which describe important narrative properties that can be used to select conflicts based on the author's purpose. We also present the results of two empirical studies which validate our operationalizations of these narrative phenomena. Finally, we demonstrate the different kinds of stories which CPOCL can produce based on constraints on the seven dimensions.}, number={3}, journal={IEEE Transactions on Computational Intelligence and AI in Games}, publisher={Institute of Electrical and Electronics Engineers (IEEE)}, author={Ware, Stephen G. and Young, R. Michael and Harrison, Brent and Roberts, David L.}, year={2014}, month={Sep}, pages={271–288} }
 @article{roberts_isbell_2014, title={Lessons on Using Computationally Generated Influence for Shaping Narrative Experiences}, volume={6}, ISSN={["1943-0698"]}, DOI={10.1109/tciaig.2013.2287154}, abstractNote={In this paper, we present computational models for generating influence that allow story managers to shape players' decisions in interactive narrative experiences. Our approach uses concepts from social psychology, discourse analysis, and natural language generation. We describe an abstract formalism to operationalize tools of social psychological influence described by Cialdini (Influence: The Psychology of Persuasion, New York, NY, USA: Harper-Collins, 1998) and evaluate two example implementations that enable a storytelling system to generate influence on the fly (with varying degrees of success), thereby adapting stories to realize goals specified by authors. These implementations are used in an interactive story where influence is generated dynamically as players' experiences unfold. We present the results of a user study to characterize the effectiveness of these models. Results did not indicate the presence of any significant differences in players' sense of control over the story with, or without, the use of influence. Further, the use of influence resulted in a set of stories experienced by players that more closely matched the author's goals.}, number={2}, journal={IEEE TRANSACTIONS ON COMPUTATIONAL INTELLIGENCE AND AI IN GAMES}, author={Roberts, David L. and Isbell, Charles L., Jr.}, year={2014}, month={Jun}, pages={188–202} }
 @article{bozkurt_roberts_sherman_brugarolas_mealin_majikes_yang_loftin_2014, title={Toward Cyber-Enhanced Working Dogs for Search and Rescue}, volume={29}, ISSN={["1941-1294"]}, DOI={10.1109/mis.2014.77}, abstractNote={The authors introduce the fundamental building blocks for a cyber-enabled, computer-mediated communication platform to connect human and canine intelligence to achieve a new generation of Cyber-Enhanced Working Dog (CEWD). The use of monitoring technologies provides handlers with real-time information about the behavior and emotional state of their CEWDs and the environments they're working in for a more intelligent canine-human collaboration. From handler to dog, haptic feedback and auditory cues are integrated to provide remote command and feedback delivery. From dog to handler, multiple inertial measurement units strategically located on a harness are used to accurately detect posture and behavior, and concurrent noninvasive photoplethysmogram and electrocardiogram for physiological monitoring. The authors also discuss how CEWDs would be incorporated with a variety of other robotic and autonomous technologies to create next-generation intelligent emergency response systems. Using cyber-physical systems to supplement and augment the two-way information exchange between human handlers and dogs would amplify the remarkable sensory capacities of search and rescue dogs and help them save more lives.}, number={6}, journal={IEEE INTELLIGENT SYSTEMS}, author={Bozkurt, Alper and Roberts, David L. and Sherman, Barbara L. and Brugarolas, Rita and Mealin, Sean and Majikes, John and Yang, Pu and Loftin, Robert}, year={2014}, pages={32–39} }
 @inproceedings{barik_everett_cardona-rivera_roberts_gehringer_2013, title={A community college blended learning classroom experience through Artificial Intelligence in Games}, ISBN={9781467352611}, url={http://dx.doi.org/10.1109/fie.2013.6685093}, DOI={10.1109/fie.2013.6685093}, abstractNote={We report on the experience of teaching an industry-validated course on Artificial Intelligence in Computer Games within the Simulation and Game Design department at a two-year community college during a 16-week semester. The course format used a blended learning just-in-time teaching approach, which included active learning programming exercises and one-on-one student interactions. Moskal's Attitudes Toward Computer Science survey showed a positive and significant increase in students in both interest (W(10) = 25, p = 0.011) and professional (W(10) = 49.5, p = 0.037) constructs. The Felder-Soloman Index of Learning Styles (n = 14) failed to identify any statistically significant differences in learning styles when compared to a four-year CS1 class. In the final class evaluation, 8 out of 13 students (62%) strongly or very strongly preferred the blended learning approach. We validated this course through four semi-structured interviews with game companies. The interview results suggest that companies are strongly favorable to the course content and structure. The results of this work serve as a template that community colleges can adopt for their curriculum.}, booktitle={2013 IEEE Frontiers in Education Conference (FIE)}, publisher={IEEE}, author={Barik, Titus and Everett, Michael and Cardona-Rivera, Rogelio E. and Roberts, David L. and Gehringer, Edward F.}, year={2013}, month={Oct} }
 @inproceedings{brugarolas_roberts_sherman_bozkurt_2013, title={Machine learning based posture estimation for a wireless canine machine interface}, DOI={10.1109/biowireless.2013.6613658}, abstractNote={Effective training and accurate interpretation of canine behaviors are essential for dog welfare and to obtain the maximum benefits provided by working dogs. We are developing a canine body area network based interface to incorporate electronic sensing and computational behavior modeling into canine training, where computers will be able to provide real time feedback to trainers about canine behavior. In this study, we investigated the accuracy of machine learning algorithms in identifying canine posture through wireless inertial sensing with 3-axis accelerometers and 3-axis gyroscopes. Data was collected from two dogs performing a sequence of 5 postures (sit, stand, lie, stand on two legs, and eat off the ground). A two-stage cascade learning technique was used: one for differentiating samples of behaviors of interest from transitions between behaviors, and one for posture classification of the behaviors. The algorithms achieved high posture classification accuracies demonstrating potential to enable a real time canine computer interface.}, booktitle={Ieee topical conference on biomedical wireless technologies networks and}, author={Brugarolas, R. and Roberts, D. and Sherman, B. and Bozkurt, A.}, year={2013}, pages={10–12} }
 @inbook{fendt_harrison_ware_cardona-rivera_roberts_2012, title={Achieving the Illusion of Agency}, ISBN={9783642348501 9783642348518}, ISSN={0302-9743 1611-3349}, url={http://dx.doi.org/10.1007/978-3-642-34851-8_11}, DOI={10.1007/978-3-642-34851-8_11}, abstractNote={Games with a strong notion of story are increasingly popular. With the increased amount of story content associated with games where player decisions significantly change the course of the game (branching games), comes an increase in the effort required to author those games. Despite the increased popularity of these kinds of games, it is unclear if a typical player is able to appreciate the rich content of these games, since any given player typically only experiences a small amount of that content. We create a non-branching game that simulates branching choices by providing players with choices followed by immediate textual feedback. We hypothesize that this game, where player decisions do not significantly change the course of the game, will maintain the player’s sense of agency. Experimentation showed that in a text-based story with forced-choice points there were in most cases no significant difference in players’ reported feelings of agency when they experience a branching story vs. a linear story with explicit acknowledgement of their choices.}, booktitle={Interactive Storytelling}, publisher={Springer Berlin Heidelberg}, author={Fendt, Matthew William and Harrison, Brent and Ware, Stephen G. and Cardona-Rivera, Rogelio E. and Roberts, David L.}, year={2012}, pages={114–125} }
 @inbook{ware_young_harrison_roberts_2012, title={Four Quantitative Metrics Describing Narrative Conflict}, ISBN={9783642348501 9783642348518}, ISSN={0302-9743 1611-3349}, url={http://dx.doi.org/10.1007/978-3-642-34851-8_2}, DOI={10.1007/978-3-642-34851-8_2}, abstractNote={Conflict is an essential element of interesting stories. In previous work, we proposed a formal model of narrative conflict along with 4 quantitative dimensions which can be used to distinguish one conflict from another based on context: balance, directness, intensity, and resolution. This paper presents the results of an experiment designed to measure how well these metrics predict the responses of human readers when asked to measure these same values in a set of four stories. We conclude that our metrics are able to rank stories similarly to human readers for each of these four dimensions.}, booktitle={Interactive Storytelling}, publisher={Springer Berlin Heidelberg}, author={Ware, Stephen G. and Young, R. Michael and Harrison, Brent and Roberts, David L.}, year={2012}, pages={18–29} }
 @inbook{roberts_roberts_2011, title={A Method for Transferring Probabilistic User Models between Environments}, ISBN={9783642252884 9783642252891}, ISSN={0302-9743 1611-3349}, url={http://dx.doi.org/10.1007/978-3-642-25289-1_6}, DOI={10.1007/978-3-642-25289-1_6}, abstractNote={Chief among the inputs to decision making algorithms in narrative or game environments is a model of player or opponent decision making. A challenge that will always face designers is to specify that model ahead of time, when actual data from the environment is likely not to be available. Absent corpora of data, designers must intuit these models as best they can, incorporating domain or expert knowledge when available. To make this process more precise, we derive a theoretically grounded technique to transfer an observed user model from one domain to another. We answer the question: “How can a model obtained from observations of one environment inform a model for another environment?” We verify the accuracy of our techniques using data from previous user studies.}, booktitle={Interactive Storytelling}, publisher={Springer Berlin Heidelberg}, author={Roberts, David L. and Roberts, Fred}, year={2011}, pages={43–54} }
 @article{roberts_roberts_2008, title={Locating sensors in paths and cycles: The case of 2-identifying codes}, volume={29}, ISSN={0195-6698}, url={http://dx.doi.org/10.1016/j.ejc.2006.12.006}, DOI={10.1016/j.ejc.2006.12.006}, abstractNote={For a graph G and a set D⊆V(G), define Nr[x]={xi∈V(G):d(x,xi)≤r} (where d(x,y) is graph theoretic distance) and Dr(x)=Nr[x]∩D. D is known as an r-identifying code if for every vertex x,Dr(x)≠0̸, and for every pair of vertices x and y, x≠y⇒Dr(x)≠Dr(y). The various applications of these codes include attack sensor placement in networks and fault detection/localization in multiprocessor or distributed systems. Bertrand et al. [N. Bertrand, I. Charon, O. Hudry, A. Lobstein, Identifying and locating–dominating codes on chains and cycles, European Journal of Combinatorics 25 (2004) 969–987] and Gravier et al. [S. Gravier, J. Moncel, A. Semri, Identifying codes of cycles, European Journal of Combinatorics 27 (2006) 767–776] provide partial results about the minimum size of D for r-identifying codes for paths and cycles and present complete closed form solutions for the case r=1, based in part on Daniel [M. Daniel, Codes identifiants, Rapport pour le DEA ROCO, Grenoble, June 2003]. We provide complete solutions for the case r=2.}, number={1}, journal={European Journal of Combinatorics}, publisher={Elsevier BV}, author={Roberts, David L. and Roberts, Fred S.}, year={2008}, month={Jan}, pages={72–82} }
 @inbook{roberts_isbell_riedl_bogost_furst_2008, title={On the Use of Computational Models of Influence for Managing Interactive Virtual Experiences}, ISBN={9783540894247 9783540894544}, ISSN={0302-9743 1611-3349}, url={http://dx.doi.org/10.1007/978-3-540-89454-4_34}, DOI={10.1007/978-3-540-89454-4_34}, abstractNote={We highlight some of the characteristics of existing technical approaches to the management of interactive experiences and motivate computational models of influence, a technique we are developing to aid drama managers in the persuasion of players to make decisions that are consistent with an author’s goals. Many of the existing approaches to managing interactive experiences have focused on the physical manipulation of the environment, but we argue instead for the use of theories from social psychology and behavioral economics to affect the adoption of specific goals by the player.}, booktitle={Interactive Storytelling}, publisher={Springer Berlin Heidelberg}, author={Roberts, David L. and Isbell, Charles and Riedl, Mark and Bogost, Ian and Furst, Merrick L.}, year={2008}, pages={268–272} }
 @article{roberts_isbell_littman_2008, title={Optimization problems involving collections of dependent objects}, volume={163}, ISSN={0254-5330 1572-9338}, url={http://dx.doi.org/10.1007/S10479-008-0350-1}, DOI={10.1007/S10479-008-0350-1}, number={1}, journal={Annals of Operations Research}, publisher={Springer Science and Business Media LLC}, author={Roberts, David L. and Isbell, Charles L., Jr. and Littman, Michael L.}, year={2008}, month={Apr}, pages={255–270} }