<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Lewis, Matthew</style></author><author><style face="normal" font="default" size="100%">Naomi Fineberg</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Robot Model of OC-Spectrum Disorders: Design Framework, Implementation and First Experiments</style></title><secondary-title><style face="normal" font="default" size="100%">Computational Psychiatry</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2019</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://cpsyjournal.org/article/10.1162/CPSY_a_00025/</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">MIT Press</style></publisher><volume><style face="normal" font="default" size="100%">3</style></volume><pages><style face="normal" font="default" size="100%">40–75</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Computational psychiatry is increasingly establishing itself as valuable discipline for understanding human mental disorders. However, robot models and their potential for investigating embodied and contextual aspects of mental health have been, to date, largely unexplored. In this paper, we present an initial robot model of obsessive-compulsive (OC) spectrum disorders based on an embodied motivation-based control architecture for decision making in autonomous robots. The OC family of conditions is chiefly characterized by obsessions (recurrent, invasive thoughts) and/or compulsions (an urge to carry out certain repetitive or ritualized behaviors). The design of our robot model follows and illustrates a general design framework that we have proposed to ground research in robot models of mental disorders, and to link it with existing methodologies in psychiatry, and notably in the design of animal models. To test and validate our model, we present and discuss initial experiments, results, and quantitative and qualitative analysis regarding the compulsive and obsessive elements of OC-spectrum disorders. While this initial stage of development only models basic elements of such disorders, our results already shed light on aspects of the underlying theoretical model that are not obvious simply from consideration of the model.</style></abstract><notes><style face="normal" font="default" size="100%">&lt;a href=&quot;https://cpsyjournal.org/article/10.1162/CPSY_a_00025/&quot;&gt;Download&lt;/a&gt; (Open Access)</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Lewis, Matthew</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Robot Model of Stress-Induced Compulsive Behavior</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. 8th International Conference on Affective Computing &amp; Intelligent Interaction (ACII 2019)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">09/2019</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://ieeexplore.ieee.org/document/8925511</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">IEEE</style></publisher><pub-location><style face="normal" font="default" size="100%">Cambridge, United Kingdom</style></pub-location><pages><style face="normal" font="default" size="100%">559–565</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Stress is one of the potential mechanisms underlying compulsive behavior in obsessive-compulsive spectrum disorders. In this paper, we present a robot model and experiments investigating the interactions between internally- and externally-induced stress and compulsive behavior. Our results show properties of the model with potential implications for understanding how stress can result in the generation and maintenance of compulsive behaviors, and how response-prevention interventions can affect compulsive responses under different conditions.</style></abstract><notes><style face="normal" font="default" size="100%">&lt;a href=&quot;https://ieeexplore.ieee.org/document/8925511&quot;&gt;Download&lt;/a&gt; (or &lt;a href=&quot;http://www.emotion-modeling.info/sites/default/files/ACII_Lewis_Canamero_2019_draft.pdf&quot;&gt;Download accepted version&lt;/a&gt;)</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Lewis, Matthew</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Robin: An Autonomous Robot for Diabetic Children</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. UK-RAS Conference: 'Robots Working For &amp; Among Us', 2017</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2018</style></year></dates><pub-location><style face="normal" font="default" size="100%">Bristol, UK</style></pub-location><pages><style face="normal" font="default" size="100%">13–15</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We describe the cognitively and motivationally autonomous robot toddler Robin, designed as a tool to help children learn about diabetes management. The design of Robin follows an Embodied Artificial Intelligence approach to robotics, to create a robust social interaction agent, friendly but independent. We have used Robin in autonomous interactions with diabetic children in a scenario designed to give them mastery experiences of diabetes management in order to increase their self-efficacy.</style></abstract><notes><style face="normal" font="default" size="100%">Winner: 1st Prize, Best Paper
&lt;a href=&quot;http://www.emotion-modeling.info/sites/default/files/UK-RAS_2017_Robin_proceedings.pdf&quot;&gt;Download&lt;/a&gt;</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Lewis, Matthew</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Robot Models of Mental Disorders</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. 7th International Conference on Affective Computing and Intelligent Interaction, Workshops and Demos (ACIIW 2017)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2017</style></year><pub-dates><date><style  face="normal" font="default" size="100%">10/2017</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://ieeexplore.ieee.org/document/8272613/</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">IEEE</style></publisher><pub-location><style face="normal" font="default" size="100%">San Antonio, TX</style></pub-location><pages><style face="normal" font="default" size="100%">193–200</style></pages><isbn><style face="normal" font="default" size="100%">978-1-5386-0680-3</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Alongside technological tools to support wellbeing and treatment of mental disorders, models of these disorders can also be invaluable tools to understand, support and improve these conditions. Robots can provide ecologically valid models that take into account embodiment-, interaction-, and context-related elements. Focusing on Obsessive-Compulsive spectrum disorders, in this paper we discuss some of the potential contributions of robot models and relate them to other models used in psychology and psychiatry, particularly animal models. We also present some initial recommendations for their meaningful design and rigorous use.</style></abstract><notes><style face="normal" font="default" size="100%">&lt;a href=&quot;http://ieeexplore.ieee.org/document/8272613/&quot;&gt;Download&lt;/a&gt; (or &lt;a href=&quot;http://www.emotion-modeling.info/sites/default/files/ACII_Lewis_Canamero_2017_Robot_Models_of_Mental_Disorders_draft.pdf&quot;&gt;Download authors' draft&lt;/a&gt;)</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Antoine Hiolle</style></author><author><style face="normal" font="default" size="100%">Lewis, Matthew</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Robot that Uses Arousal to Detect Learning Challenges and Seek Help</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. 14th Conference on the Synthesis and Simulation of Living Systems (ALIFE 2014)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.mitpressjournals.org/doi/abs/10.1162/978-0-262-32621-6-ch142</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">MIT Press</style></publisher><pub-location><style face="normal" font="default" size="100%">New York, NY</style></pub-location><pages><style face="normal" font="default" size="100%">864–871</style></pages><isbn><style face="normal" font="default" size="100%">978-0-262-32621-6</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">In the context of our work on dyadic robot-human (caregiver) interaction from a developmental robotics perspective, in this paper we investigate how an autonomous robot that explores and learns novel environments can make use of its arousal system to detect situations that constitute learning challenges, and request help from a human at points where this help is most needed and can be most beneficial. In a set of experiments, our robot learns to classify and recognize the perceptual properties of various objects placed on a table. We show that the arousal system of the robot permits it to identify and react to incongruent and novel features in the environment. More specifically, our results show that the robot identifies perceived outliers and episodic perceptual anomalies. As in the case of young infants, arousal variations trigger regulatory behaviours that engage caregivers in helping behaviors. We conclude that this attachment-based architecture provides a generic process that permits a robot to request interventions from a human caregiver during relevant events.</style></abstract><notes><style face="normal" font="default" size="100%">&lt;a href=&quot;https://www.mitpressjournals.org/doi/abs/10.1162/978-0-262-32621-6-ch142&quot;&gt;Download&lt;/a&gt;</style></notes></record></records></xml>