@inproceedings {9998, title = {Adaptation and the Social Salience Hypothesis of Oxytocin: Early Experiments in a Simulated Agent Environment}, booktitle = {Proc. 2nd Symposium on Social Interactions in Complex Intelligent Systems (SICIS)}, series = {Proc. 2018 Convention of the Society for the Study of Artificial Intelligence and Simulation of Behaviour (AISB 2018)}, year = {2018}, note = {Download full proceedings (PDF)}, month = {04/2018}, pages = {2{\textendash}9}, address = {Liverpool, UK}, abstract = {Allostasis is a mechanism that permits adaptation of an organism as a response to changing (physical or social) environmental conditions. Allostasis is driven by a number of factors, including regulation through hormonal mechanisms. Oxytocin (OT) is a hormone that has been found to play a role in regulating social behaviours and adaptation. However, the concrete effects that OT promotes remain unclear and controversial. One of these effects is on the attention paid to social cues (social salience). Two opposing hypotheses have been proposed. One hypothesis is that adaptation is achieved by increasing attention to social cues (increasing social salience), the other that adaptation is achieved by decreasing attention to social cues (decreasing social salience). In this paper, we present agent simulation experiments that test these two contrasting hypotheses under different environmental conditions related to food availability: a comfortable environment, a challenging environment, and a very challenging environment. Our results show that, for the particular conditions modelled, increased social salience through the release of simulated oxytocin presents significant advantages in the challenging conditions.}, url = {http://aisb2018.csc.liv.ac.uk/PROCEEDINGS\%20AISB2018/Social\%20Interactions\%20in\%20Complex\%20Intelligent\%20Systems\%20(SICIS)\%20-\%20AISB2018.pdf}, author = {Imran Khan and Lewis, Matthew and Lola Ca{\~n}amero} } @inproceedings {4, title = {An Affective Autonomous Robot Toddler to Support the Development of Self-Efficacy in Diabetic Children}, booktitle = {Proc. 23rd Annual IEEE International Symposium on Robot and Human Interactive Communication (IEEE RO-MAN 2014)}, year = {2014}, note = {Download (or Download authors{\textquoteright} draft)}, month = {08/2014}, pages = {359{\textendash}364}, publisher = {IEEE}, organization = {IEEE}, address = {Edinburgh}, abstract = {We present a software architecture and an interaction scenario for an autonomous robot toddler designed to support the development of self-efficacy in diabetic children, and discuss its potential medical benefits. We pay particular attention to the affective and social aspects of the interaction, as well as the importance of autonomy in the robot, examining their relationships to our scientific and therapeutic goals.}, isbn = {978-1-4799-6763-6}, doi = {10.1109/ROMAN.2014.6926279}, url = {http://ieeexplore.ieee.org/document/6926279/}, author = {Lewis, Matthew and Lola Ca{\~n}amero} } @article {2014, title = {Arousal Regulation and Affective Adaptation to Human Responsiveness by a Robot that Explores and Learns a Novel Environment}, journal = {Frontiers in Neurorobotics}, volume = {8}, year = {2014}, note = {Download (Open Access)}, pages = {17}, abstract = {In the context of our work in developmental robotics regarding robot-human caregiver interactions, in this paper we investigate how a "baby" robot that explores and learns novel environments can adapt its affective regulatory behavior of soliciting help from a "caregiver" to the preferences shown by the caregiver in terms of varying responsiveness. We build on two strands of previous work that assessed independently (a) the differences between two "idealized" robot profiles {\textendash} a "needy" and an "independent" robot {\textendash} in terms of their use of a caregiver as a means to regulate the "stress" (arousal) produced by the exploration and learning of a novel environment, and (b) the effects on the robot behaviors of two caregiving profiles varying in their responsiveness {\textendash} "responsive" and "non-responsive" {\textendash} to the regulatory requests of the robot. Going beyond previous work, in this paper we (a) assess the effects that the varying regulatory behavior of the two robot profiles has on the exploratory and learning patterns of the robots; (b) bring together the two strands previously investigated in isolation and take a step further by endowing the robot with the capability to adapt its regulatory behavior along the "needy" and "independent" axis as a function of the varying responsiveness of the caregiver; and (c) analyze the effects that the varying regulatory behavior has on the exploratory and learning patterns of the adaptive robot.}, issn = {1662-5218}, doi = {10.3389/fnbot.2014.00017}, url = {http://journal.frontiersin.org/article/10.3389/fnbot.2014.00017}, author = {Antoine Hiolle and Lewis, Matthew and Lola Ca{\~n}amero} } @inproceedings {2013, title = {Are Discrete Emotions Useful in Human-Robot Interaction? Feedback from Motion Capture Analysis}, booktitle = {Proc. Affective Computing and Intelligent Interaction (ACII 2013)}, year = {2013}, note = {Download (or Download authors{\textquoteright} draft)}, month = {09/2013}, pages = {97{\textendash}102}, publisher = {IEEE}, organization = {IEEE}, address = {Geneva, Switzerland}, abstract = {We have conducted a study analyzing motion capture data of bodily expressions of human emotions towards the goal of building a social expressive robot that interacts with and supports hospitalized children. Although modeling emotional expression (and recognition) in (by) robots in terms of discrete categories presents advantages such as ease and clarity of interpretation, our results show that this approach also poses a number of problems. The main issues relate to the loss of subtle expressions and feelings, individual features, context, and social interaction elements that are present in real life.}, doi = {10.1109/ACII.2013.23}, url = {https://ieeexplore.ieee.org/document/6681414}, author = {Lewis, Matthew and Lola Ca{\~n}amero} }