| 1. |
- Birney, Ewan, et al.
(author)
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Identification and analysis of functional elements in 1% of the human genome by the ENCODE pilot project
- 2007
-
In: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 447:7146, s. 799-816
-
Journal article (peer-reviewed)abstract
- We report the generation and analysis of functional data from multiple, diverse experiments performed on a targeted 1% of the human genome as part of the pilot phase of the ENCODE Project. These data have been further integrated and augmented by a number of evolutionary and computational analyses. Together, our results advance the collective knowledge about human genome function in several major areas. First, our studies provide convincing evidence that the genome is pervasively transcribed, such that the majority of its bases can be found in primary transcripts, including non-protein-coding transcripts, and those that extensively overlap one another. Second, systematic examination of transcriptional regulation has yielded new understanding about transcription start sites, including their relationship to specific regulatory sequences and features of chromatin accessibility and histone modification. Third, a more sophisticated view of chromatin structure has emerged, including its inter-relationship with DNA replication and transcriptional regulation. Finally, integration of these new sources of information, in particular with respect to mammalian evolution based on inter- and intra-species sequence comparisons, has yielded new mechanistic and evolutionary insights concerning the functional landscape of the human genome. Together, these studies are defining a path for pursuit of a more comprehensive characterization of human genome function.
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| 2. |
- Tobias, Deirdre K, et al.
(author)
-
Second international consensus report on gaps and opportunities for the clinical translation of precision diabetes medicine
- 2023
-
In: Nature Medicine. - 1546-170X. ; 29:10, s. 2438-2457
-
Research review (peer-reviewed)abstract
- Precision medicine is part of the logical evolution of contemporary evidence-based medicine that seeks to reduce errors and optimize outcomes when making medical decisions and health recommendations. Diabetes affects hundreds of millions of people worldwide, many of whom will develop life-threatening complications and die prematurely. Precision medicine can potentially address this enormous problem by accounting for heterogeneity in the etiology, clinical presentation and pathogenesis of common forms of diabetes and risks of complications. This second international consensus report on precision diabetes medicine summarizes the findings from a systematic evidence review across the key pillars of precision medicine (prevention, diagnosis, treatment, prognosis) in four recognized forms of diabetes (monogenic, gestational, type 1, type 2). These reviews address key questions about the translation of precision medicine research into practice. Although not complete, owing to the vast literature on this topic, they revealed opportunities for the immediate or near-term clinical implementation of precision diabetes medicine; furthermore, we expose important gaps in knowledge, focusing on the need to obtain new clinically relevant evidence. Gaps include the need for common standards for clinical readiness, including consideration of cost-effectiveness, health equity, predictive accuracy, liability and accessibility. Key milestones are outlined for the broad clinical implementation of precision diabetes medicine.
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| 3. |
- Machiela, Mitchell J., et al.
(author)
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Characterization of Large Structural Genetic Mosaicism in Human Autosomes
- 2015
-
In: American Journal of Human Genetics. - : Elsevier BV. - 0002-9297 .- 1537-6605. ; 96:3, s. 487-497
-
Journal article (peer-reviewed)abstract
- Analyses of genome-wide association study (GWAS) data have revealed that detectable genetic mosaicism involving large (>2 Mb) structural autosomal alterations occurs in a fraction of individuals. We present results for a set of 24,849 genotyped individuals (total GWAS set II [TGSII]) in whom 341 large autosomal abnormalities were observed in 168 (0.68%) individuals. Merging data from the new TGSII set with data from two prior reports (the Gene-Environment Association Studies and the total GWAS set I) generated a large dataset of 127,179 individuals; we then conducted a meta-analysis to investigate the patterns of detectable autosomal mosaicism (n = 1,315 events in 925 [0.73%] individuals). Restricting to events >2 Mb in size, we observed an increase in event frequency as event size decreased. The combined results underscore that the rate of detectable mosaicism increases with age (p value = 5.5 x 3 10(-31)) and is higher in men (p value = 0.002) but lower in participants of African ancestry (p value = 0.003). In a subset of 47 individuals from whom serial samples were collected up to 6 years apart, complex changes were noted over time and showed an overall increase in the proportion of mosaic cells as age increased. Our large combined sample allowed for a unique ability to characterize detectable genetic mosaicism involving large structural events and strengthens the emerging evidence of non-random erosion of the genome in the aging population.
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| 4. |
- Kilpeläinen, Tuomas O, et al.
(author)
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Genome-wide meta-analysis uncovers novel loci influencing circulating leptin levels
- 2016
-
In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 7
-
Journal article (peer-reviewed)abstract
- Leptin is an adipocyte-secreted hormone, the circulating levels of which correlate closely with overall adiposity. Although rare mutations in the leptin (LEP) gene are well known to cause leptin deficiency and severe obesity, no common loci regulating circulating leptin levels have been uncovered. Therefore, we performed a genome-wide association study (GWAS) of circulating leptin levels from 32,161 individuals and followed up loci reaching P<10(-6) in 19,979 additional individuals. We identify five loci robustly associated (P<5 × 10(-8)) with leptin levels in/near LEP, SLC32A1, GCKR, CCNL1 and FTO. Although the association of the FTO obesity locus with leptin levels is abolished by adjustment for BMI, associations of the four other loci are independent of adiposity. The GCKR locus was found associated with multiple metabolic traits in previous GWAS and the CCNL1 locus with birth weight. Knockdown experiments in mouse adipose tissue explants show convincing evidence for adipogenin, a regulator of adipocyte differentiation, as the novel causal gene in the SLC32A1 locus influencing leptin levels. Our findings provide novel insights into the regulation of leptin production by adipose tissue and open new avenues for examining the influence of variation in leptin levels on adiposity and metabolic health.
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| 5. |
- Alenljung, Beatrice, 1971-, et al.
(author)
-
Conveying Emotions by Touch to the Nao Robot : A User Experience Perspective
- 2018
-
In: Multimodal Technologies and Interaction. - : MDPI. - 2414-4088. ; 2:4
-
Journal article (peer-reviewed)abstract
- Social robots are expected gradually to be used by more and more people in a widerrange of settings, domestic as well as professional. As a consequence, the features and qualityrequirements on human–robot interaction will increase, comprising possibilities to communicateemotions, establishing a positive user experience, e.g., using touch. In this paper, the focus is ondepicting how humans, as the users of robots, experience tactile emotional communication with theNao Robot, as well as identifying aspects affecting the experience and touch behavior. A qualitativeinvestigation was conducted as part of a larger experiment. The major findings consist of 15 differentaspects that vary along one or more dimensions and how those influence the four dimensions ofuser experience that are present in the study, as well as the different parts of touch behavior ofconveying emotions.
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| 6. |
- Alenljung, Beatrice, et al.
(author)
-
User Experience of Conveying Emotions by Touch
- 2017
-
In: Proceedings of the 26th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN). - : IEEE. - 9781538635179 - 9781538635193 - 9781538635186 ; , s. 1240-1247
-
Conference paper (peer-reviewed)abstract
- In the present study, 64 users were asked to convey eight distinct emotion to a humanoid Nao robot via touch, and were then asked to evaluate their experiences of performing that task. Large differences between emotions were revealed. Users perceived conveying of positive/pro-social emotions as significantly easier than negative emotions, with love and disgust as the two extremes. When asked whether they would act differently towards a human, compared to the robot, the users’ replies varied. A content analysis of interviews revealed a generally positive user experience (UX) while interacting with the robot, but users also found the task challenging in several ways. Three major themes with impact on the UX emerged; responsiveness, robustness, and trickiness. The results are discussed in relation to a study of human-human affective tactile interaction, with implications for human-robot interaction (HRI) and design of social and affective robotics in particular.
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| 7. |
- Andersson, Lena, et al.
(author)
-
Pancreatic lipase related protein 2, but not classical lipase hydrolyzes galactolipids
- 1996
-
In: Biochimica et Biophysica Acta. - : Elsevier BV. - 0006-3002. ; 1302:3, s. 236-240
-
Journal article (peer-reviewed)abstract
- The pancreatic lipase family contains three subfamilies, the 'classical' lipases and the pancreatic lipase-related proteins 1 (PLRP1) and 2 (PLRP2). Galactolipids are present in membranes of leaves and vegetables and consist of digalactosyldiacylglycerol (DGalDG) monogalactosyldiacylglycerol (MGalDG) and sulfoquinovosyldiacylglycerol (SQDG). These lipids were incubated with PLRP2 from guinea-pig (GPLRP2) and rat (RPLRP2). In the presence of bile salts DGalDG was efficiently hydrolyzed by GPLRP2 and, although less efficiently, by RPLRP2 to digalactosylmonoacylglycerol (DGalMG), free fatty acids and water-soluble galactose-containing compounds. Also, MGalDG and SQDG were hydrolyzed by GPLRP2 and RPLRP2. These data suggest a possible role of PLRP2 in the digestion of dietary galactolipids
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| 8. |
- Andreasson, Rebecca, et al.
(author)
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Affective Touch in Human-Robot Interaction: Conveying Emotion to the Nao Robot
- 2018
-
In: International Journal of Social Robotics. - : Springer Science and Business Media LLC. - 1875-4791 .- 1875-4805. ; 10:4, s. 473-491
-
Journal article (peer-reviewed)abstract
- Affective touch has a fundamental role in human development, social bonding, and for providing emotional support in interpersonal relationships. We present, what is to our knowledge, the first HRI study of tactile conveyance of both positive and negative emotions (affective touch) on the Nao robot, and based on an experimental set-up from a study of human-human tactile communication. In the present work, participants conveyed eight emotions to a small humanoid robot via touch. We found that female participants conveyed emotions for a longer time, using more varied interaction and touching more regions on the robot's body, compared to male participants. Several differences between emotions were found such that emotions could be classified by the valence of the emotion conveyed, by combining touch amount and duration. Overall, these results show high agreement with those reported for human-human affective tactile communication and could also have impact on the design and placement of tactile sensors on humanoid robots.
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| 9. |
- Bedford, Lynn, et al.
(author)
-
Depletion of 26S proteasomes in mouse brain neurons causes neurodegeneration and Lewy-like inclusions resembling human pale bodies
- 2008
-
In: Journal of Neuroscience. - 0270-6474 .- 1529-2401. ; 28:33, s. 8189-98
-
Journal article (peer-reviewed)abstract
- Ubiquitin-positive intraneuronal inclusions are a consistent feature of the major human neurodegenerative diseases, suggesting that dysfunction of the ubiquitin proteasome system is central to disease etiology. Research using inhibitors of the 20S proteasome to model Parkinson's disease is controversial. We report for the first time that specifically 26S proteasomal dysfunction is sufficient to trigger neurodegenerative disease. Here, we describe novel conditional genetic mouse models using the Cre/loxP system to spatially restrict inactivation of Psmc1 (Rpt2/S4) to neurons of either the substantia nigra or forebrain (e.g., cortex, hippocampus, and striatum). PSMC1 is an essential subunit of the 26S proteasome and Psmc1 conditional knock-out mice display 26S proteasome depletion in targeted neurons, in which the 20S proteasome is not affected. Impairment of specifically ubiquitin-mediated protein degradation caused intraneuronal Lewy-like inclusions and extensive neurodegeneration in the nigrostriatal pathway and forebrain regions. Ubiquitin and alpha-synuclein neuropathology was evident, similar to human Lewy bodies, but interestingly, inclusion bodies contained mitochondria. We support this observation by demonstrating mitochondria in an early form of Lewy body (pale body) from Parkinson's disease patients. The results directly confirm that 26S dysfunction in neurons is involved in the pathology of neurodegenerative disease. The model demonstrates that 26S proteasomes are necessary for normal neuronal homeostasis and that 20S proteasome activity is insufficient for neuronal survival. Finally, we are providing the first reproducible genetic platform for identifying new therapeutic targets to slow or prevent neurodegeneration.
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| 10. |
- Billing, Erik, 1981-, et al.
(author)
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Finding Your Way from the Bed to the Kitchen: Reenacting and Recombining Sensorimotor Episodes Learned from Human Demonstration
- 2016
-
In: Frontiers in Robotics and Ai. - Lausanne, Switzerland : Frontiers Media SA. - 2296-9144. ; 3
-
Journal article (peer-reviewed)abstract
- Several simulation theories have been proposed as an explanation for how humans and other agents internalize an "inner world" that allows them to simulate interactions with the external real world - prospectively and retrospectively. Such internal simulation of interaction with the environment has been argued to be a key mechanism behind mentalizing and planning. In the present work, we study internal simulations in a robot acting in a simulated human environment. A model of sensory-motor interactions with the environment is generated from human demonstrations and tested on a Robosoft Kompai robot. The model is used as a controller for the robot, reproducing the demonstrated behavior. Information from several different demonstrations is mixed, allowing the robot to produce novel paths through the environment, toward a goal specified by top-down contextual information. The robot model is also used in a covert mode, where the execution of actions is inhibited and perceptions are generated by a forward model. As a result, the robot generates an internal simulation of the sensory-motor interactions with the environment. Similar to the overt mode, the model is able to reproduce the demonstrated behavior as internal simulations. When experiences from several demonstrations are combined with a top-down goal signal, the system produces internal simulations of novel paths through the environment. These results can be understood as the robot imagining an "inner world" generated from previous experience, allowing it to try out different possible futures without executing actions overtly. We found that the success rate in terms of reaching the specified goal was higher during internal simulation, compared to overt action. These results are linked to a reduction in prediction errors generated during covert action. Despite the fact that the model is quite successful in terms of generating covert behavior toward specified goals, internal simulations display different temporal distributions compared to their overt counterparts. Links to human cognition and specifically mental imagery are discussed.
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| 11. |
- Billing, Erik, 1981-, et al.
(author)
-
Simultaneous planning and action: neural-dynamic sequencing of elementary behaviors in robot navigation
- 2015
-
In: Adaptive Behavior. - : SAGE Publications. - 1059-7123 .- 1741-2633. ; 23:5, s. 243-264
-
Journal article (peer-reviewed)abstract
- A technique for simultaneous planning and action based on dynamic field theory is presented. The model builds on previous work on representation of sequential behavior as attractors in dynamic neural fields. Here, we demonstrate how chains of competing attractors can be used to represent dynamic plans towards a goal state. The present work can be seen as an addition to a growing body of work that demonstrates the role of dynamic field theory as a bridge between low-level reactive approaches and high-level symbol processing mechanisms. The architecture is evaluated on a set of planning problems using a simulated e-puck robot, including analysis of the system's behavior in response to noise and temporary blockages of the planned route. The system makes no explicit distinction between planning and execution phases, allowing continuous adaptation of the planned path. The proposed architecture exploits the dynamic field theory property of stability in relation to noise and changes in the environment. The neural dynamics are also exploited such that stay-or-switch action selection emerges where blockage of a planned path occurs; stay until the transient blockage is removed versus switch to an alternative route to the goal.
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| 12. |
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| 13. |
- Bourlat, Sarah, et al.
(author)
-
Deuterostome phylogeny reveals monophyletic chordates and the new phylum Xenoturbellida
- 2006
-
In: Nature. ; 444:7115, s. 85-88
-
Journal article (peer-reviewed)abstract
- Deuterostomes comprise vertebrates, the related invertebrate chordates (tunicates and cephalochordates) and three other inver- tebrate taxa: hemichordates, echinoderms and Xenoturbella1. The relationships between invertebrate and vertebrate deuterostomes are clearly important for understanding our own distant origins. Recent phylogenetic studies of chordate classes and a sea urchin have indicated that urochordates might be the closest inverte- brate sister group of vertebrates, rather than cephalochordates, as traditionally believed2–5. More remarkable is the suggestion that cephalochordates are closer to echinoderms than to vertebrates and urochordates, meaning that chordates are paraphyletic2. To study the relationships among all deuterostome groups, we have assembled an alignment of more than 35,000 homologous amino acids, including new data from a hemichordate, starfish and Xenoturbella. We have also sequenced the mitochondrial genome of Xenoturbella. We support the clades Olfactores (urochordates and vertebrates) and Ambulacraria (hemichordates and echino- derms6). Analyses using our new data, however, do not support a cephalochordate and echinoderm grouping and we conclude that chordates are monophyletic. Finally, nuclear and mitochondrial data place Xenoturbella as the sister group of the two ambulacrar- ian phyla1. As such, Xenoturbella is shown to be an independent phylum, Xenoturbellida, bringing the number of living deutero- stome phyla to four.
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| 14. |
- Clark, Douglas S., et al.
(author)
-
Klaus Mosbach Tribute
- 2015
-
In: Biotechnology and Bioengineering. - : Wiley. - 1097-0290 .- 0006-3592. ; 112:4, s. 645-647
-
Journal article (other academic/artistic)
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| 15. |
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| 16. |
- Dodig Crnkovic, Gordana, 1955, et al.
(author)
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Morphological Computing and Cognitive Agency
- 2017
-
In: Proceedings (MDPI). - Gothenburg, Sweden : MDPI. - 2504-3900. ; 1:3, s. 185-188
-
Journal article (peer-reviewed)abstract
- Morphological computing, at its core, entails that the morphology (shape + material properties) of an agent (a living organism or a machine) enables and constrains its possible (physical and social)interactions with the environment as well as its development, including its growth and reconfiguration. The role of such computation in cognitive systems includes the off-loading of control onto the body and its interaction with the environment thus enabling flexible and adaptivebehavior. In a more general sense, cognitive agency instantiated by the interaction processes of morphological structures in networks of networks of cognitive agents from cells to organisms and societies is a basis of understanding of embodiment of cognition on variety of levels of (self-)organisation of physical matter from its basic physical structures via chemistry and biology with life itself as cognitive process.
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| 17. |
- Durán, Boris, et al.
(author)
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Learning a DFT-based sequence with reinforcement learning : A NAO implementation
- 2012
-
In: Paladyn - Journal of Behavioral Robotics. - : Springer. - 2080-9778 .- 2081-4836. ; 3:4, s. 181-187
-
Journal article (peer-reviewed)abstract
- The implementation of sequence learning in robotic platforms offers several challenges. Deciding when to stop one action and continue to the next requires a balance between stability of sensory information and, of course, the knowledge about what action is required next. The work presented here proposes a starting point for the successful execution and learning of dynamic sequences. Making use of the NAO humanoid platform we propose a mathematical model based on dynamic field theory and reinforcement learning methods for obtaining and performing a sequence of elementary motor behaviors. Results from the comparison of two reinforcement learning methods applied to sequence generation, for both simulation and implementation, are provided.
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| 18. |
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| 19. |
- Gander, Pierre, 1971, et al.
(author)
-
A framework for memory of fictional information
- 2022
-
In: Poster presented at the Psychonomic Society's 63rd Annual Meeting, Boston, Massachusetts, USA, Nov. 17–20, 2022..
-
Conference paper (other academic/artistic)
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| 20. |
- Gander, Pierre, 1971, et al.
(author)
-
A social differential outcomes learning task: Performance, EEG, and questionnaire data
- 2020
-
In: Data in Brief. - : Elsevier BV. - 2352-3409. ; 33
-
Journal article (peer-reviewed)abstract
- This article contains performance data, questionnaire ratings, and EEG data from a differential outcomes learning task from two experiments. In both experiments, the standard differential outcomes learning task was extended to involve a social dimension, in order to capture how people can learn from others by observation. In Experiment 1 (N=20), using a within-subjects design, participants learned pairings of image stimuli in four conditions: 1) individual-differential outcomes, 2) individual-non-differential outcomes, 3) social-differential outcomes, and 4) social-non-differential outcomes. The social condition had a screen-captured video recording of the outcomes (but not the actions themselves) of another person performing the task. During the task, the performance of the participants was measured. After the task, participants rated their experience in a questionnaire. The procedure for Experiment 2 (N=33) was similar to Experiment 1, but with a stronger social manipulation using a video of another person's face showing facial expressions reflecting the outcomes. In addition, EEG was measured while performing the task. For more insight, please see Vicarious value learning: Knowledge transfer through affective processing on a social differential outcomes task (Rittmo et al., 2020).
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| 21. |
- Gander, Pierre, 1971, et al.
(author)
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Differences in experienced memory qualities between factual and fictional events
- 2023
-
In: Journal of Cognition and Culture. - 1567-7095. ; 23:3–4, s. 378-396
-
Journal article (peer-reviewed)abstract
- The experienced qualities of memories of factual and fictional events have been little researched previously. The few studies that exist find no or few differences. However, one reason to expect differences in memory qualities is that processing of fact and fiction seem to involve activation of different brain areas. The present study expands earlier research by including a wider range of memory qualities, using positive and negative events, and three time-points: immediately after, after a ten-minute delay and after a five-week delay. Participants (N = 52) read four short stories in English, labelled either fact or fiction, and rated memory qualities on 7-point scales. Results show no differences; however, an interaction was found between fictionality and story emotional valence, in that memories of negative fictional stories are rated as more clear. The higher clarity can be explained by previous findings that negative events from stories are in general remembered in more detail, in combination with the idea that fiction entails simulation to a higher degree than fact. The conclusion is that although a difference in memory qualities between fact and fiction was found in one case, memory qualities seem not to play an operative role when the memory system distinguishes fact from fiction.
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| 22. |
- Gander, Pierre, 1971, et al.
(author)
-
Memory of Fictional Information: A Theoretical Framework
- 2023
-
In: Perspectives on Psychological Science. - 1745-6916 .- 1745-6924.
-
Journal article (peer-reviewed)abstract
- Much of the information people encounter in everyday life is not factual; it originates from fictional sources, such as movies, novels, and video games, and from direct experience such as pretense, role-playing, and everyday conversation. Despite the recent increase in research on fiction, there is no theoretical account of how memory of fictional information is related to other types of memory or of which mechanisms allow people to separate fact and fiction in memory. We present a theoretical framework that places memory of fiction in relation to other cognitive phenomena as a distinct construct and argue that it is an essential component for any general theory of human memory. We show how fictionality can be integrated in an existing memory model by extending Rubin’s dimensional conceptual memory model. By this means, our model can account for explicit and implicit memory of fictional information of events, places, characters, and objects. Further, we propose a set of mechanisms involving various degrees of complexity and levels of conscious processing that mostly keep fact and fiction separated but also allow information from fiction to influence real-world attitudes and beliefs: content-based reasoning, source monitoring, and an associative link from the memory to the concept of fiction.
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| 23. |
- Gander, Pierre, 1971, et al.
(author)
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What kind of memory is memory of fiction?
- 2022
-
In: Presented at the Annual Meeting of the Swedish Cognitive Science Society.
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Conference paper (other academic/artistic)
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| 24. |
- Kiryazov, Kiril, et al.
(author)
-
From the virtual to the robotic : Bringing emoting and appraising agents into reality
- 2011
-
In: Proceedings of the 2nd European Future Technologies Conference and Exhibition 2011 (FET 11). - : Elsevier. ; , s. 241-243
-
Conference paper (peer-reviewed)abstract
- - A classical appraisal model of emotions extended with artificial metabolic mechanisms is presented. The new architecture is based on two existing models: WASABI and a model of Microbial Fuel Cell technology. WASABI is a top-down cognitive model which is implemented in several virtual world applications such as a museum guide. Microbial fuel cells provide energy for the robot through digesting food. The presented work is a first step towards imbuing a physical robot with emotions of human-like complexity. Classically, such integration has only been attempted in the virtual domain. The research aim is to study the embodied appraisal theory and to show the role of the body in the emotion mechanisms. Some initial tests of the architecture with humanoid NAO robot in a minimalistic scenario are presented. © Selection and peer-review under responsibility of FET11 conference organizers and published by Elsevier B.V.
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| 25. |
- Kiryazov, Kiril
(author)
-
Grounding Emotion Appraisal in Autonomous Humanoids
- 2014
-
Licentiate thesis (other academic/artistic)abstract
- The work presented in this dissertation investigates the problem for resource management of autonomous robots. Acting under the constraint of limited resources is a necessity for every robot which should perform tasks independent of human control. Some of the most important variables and performance criteria for adaptive behavior under resource constraints are discussed. Concepts like autonomy, self-sufficiency, energy dynamics, work utility, effort of action, and optimal task selection are defined and analyzed as the emphasis is on the resource balance in interaction with a human. The primary resource for every robot is its energy. In addition to the regulation of its “energy homeostasis”, a robot should perform its designer’s tasks with the required level of efficiency. A service robot residing in a human-centered environment should perform some social tasks like cleaning, helping elderly people or delivering goods. Maintaining a proper quality of work and, at the same time, not running out of energy represents a basic two-resource problem which was used as a test-bed scenario in the thesis. Safety is an important aspect of any human-robot interaction. Thus, a new three – resource problem (energy, work quality, safety) is presented and also used for the experimental investigations in the thesis.The main contribution of the thesis is developing an affective cognitive architecture. The architecture uses top-down ethological models of action selection. The action selection mechanisms are nested into a model of human affect based on appraisal theory of emotion. The arousal component of the architecture is grounded into electrical energy processes in the robotic body and is modulating the effort of movement. The provided arousal mechanism has an important functional role for the adaptability of the robot in the proposed two- and three resource scenarios. These investigations are part of a more general goal of grounding highlevel emotion substrates - Pleasure Arousal Dominance emotion space in homeostatic processes in humanoid robots. The development of the architecture took inspiration from several computation architectures of emotion in robotics, which are analyzed in the thesis.Sustainability of the basic cycles of the essential variables of a robotic system is chosen as a basic performance measure for validating the emotion components of the architecture and the grounding process. Several experiments are performed with two humanoid robots – iCub and NAO showing the role of task selection mechanism and arousal component of the architecture for the robot’s self-sufficiency and adaptability.
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| 26. |
- Kiryazov, Kiril, et al.
(author)
-
Modelling Embodied Appraisal in Humanoids : Grounding PAD space for Augmented Autonomy
- 2011
-
In: Proceedings of the Workshop on Standards in Emotion Modeling, 2011.
-
Conference paper (other academic/artistic)abstract
- A computational emotion architecture is presented which grounds an aspect of an appraisal theoretic architecture in energy related processes. The incorporation of an energy constraint on emotional-cognitive behaviour allows greater potential for autonomous agency when implemented on a physical (NAO) robot platform. In this paper we present an algorithm that enables metabolic grounding of the arousal component of the PAD emotion space used in the architecture. We describe an exemplar problem that abstracts variables and performance criteria relevant to service robotics applications. Future work on further integration based on neurobiological grounding is discussed as well as means by which the exemplar scenario may be scaled up to more realistic service robotics based scenarios.
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| 27. |
- Kiryazov, Kiril, et al.
(author)
-
The role of arousal in embodying the cueXdeficit model in multi-resource human robot interaction
- 2013
-
In: Advances in Artificial Life, ECAL 2013, Proceedings of the Twelfth European Conference on the Synthesis and Simulation of Living System. - : MIT Press. ; , s. 19-26, s. 19-26
-
Conference paper (peer-reviewed)abstract
- In this paper is investigated the problem of managing limited resources in human-robot interaction with a computational architecture of emotion. The architecture is based on the appraisal theory of affect and an ethological motivational model of task selection. Key variables and performance criteria for robotic energy autonomous behaviour in interaction with humans are discussed. The role of arousal for modulating effort of movement is explored. It is shown that the architecture can manage task selection and the effort of the movement and offers sustainable basic-cycles in exemplar "two-resource problem" test-bed scenarios for an iCub robot. An extension of the architecture with a third "resource"—safety—is presented and how the architecture is able to solve the new "three-resource" problem is demonstrated.
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| 28. |
- Kiryazov, Kiril, et al.
(author)
-
The role of arousal in two-resource problem tasks for humanoid service robots
- 2013
-
In: IEEE RO-MAN 2013. - : IEEE. - 9781479905096 ; , s. 62-69
-
Conference paper (peer-reviewed)abstract
- A computational architecture of emotion is presented which grounds a component of an appraisal cognitive model into the homeostatic processes of a humanoid robot. The focus of the present work entails a `grounding' of the arousal component of the Pleasure Arousal Dominance emotion space into the electrical energy processes of an iCub robot. Key variables and performance criteria for robotic energy autonomous behavior in interaction with human are discussed. We show that our bio-inspired affective architecture offers viable basic cycles in exemplar “two-resource problem” testbed scenarios for a real iCub robot. The expression of the robot's emotional state and its role for the efficient interaction in the proposed two-resource problem task is discussed and experimental designs are presented.
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| 29. |
- Lee, Gauss, et al.
(author)
-
Modelling Early Infant Walking : Testing a Generic CPG Architecture on the NAO Humanoid
- 2011
-
In: IEEE International Conference on Development and Learning (ICDL), 2011. - : IEEE conference proceedings. - 9781612849898 ; , s. 1-6
-
Conference paper (peer-reviewed)abstract
- In this article, a simple CPG network is shown to model early infant walking, in particular the onset of independent walking. The difference between early infant walking and early adult walking is addressed with respect to the underlying neurophysiology and evaluated according to gait attributes. Based on this, we successfully model the early infant walking gait on the NAO robot and compare its motion dynamics and performance to those of infants. Our model is able to capture the core properties of early infant walking. We identify differences in the morphologies between the robot and infant and the effect of this on their respective performance. In conclusion, early infant walking can be seen to develop as a function of the CPG network and morphological characteristics.
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| 30. |
- Li, Cai, et al.
(author)
-
A novel approach to locomotion learning: Actor-Critic architecture using central pattern generators and dynamic motor primitives
- 2014
-
In: Frontiers in Neurorobotics. - : Frontiers. - 1662-5218. ; 8
-
Journal article (peer-reviewed)abstract
- In this article, we propose an architecture of a bio-inspired controller that addresses the problem of learning different locomotion gaits for different robot morphologies. The modeling objective is split into two: baseline motion modeling and dynamics adaptation. Baseline motion modeling aims to achieve fundamental functions of a certain type of locomotion and dynamics adaptation provides a "reshaping" function for adapting the baseline motion to desired motion. Based on this assumption, a three-layer architecture is developed using central pattern generators (CPGs, a bio-inspired locomotor center for the baseline motion) and dynamic motor primitives (DMPs, a model with universal "reshaping" functions). In this article, we use this architecture with the actor-critic algorithms for finding a good "reshaping" function. In order to demonstrate the learning power of the actor-critic based architecture, we tested it on two experiments: (1) learning to crawl on a humanoid and, (2) learning to gallop on a puppy robot. Two types of actor-critic algorithms (policy search and policy gradient) are compared in order to evaluate the advantages and disadvantages of different actor-critic based learning algorithms for different morphologies. Finally, based on the analysis of the experimental results, a generic view/architecture for locomotion learning is discussed in the conclusion.
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| 31. |
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| 32. |
- Li, Cai, et al.
(author)
-
Crawling Posture Learning in Humanoid Robots using a Natural-Actor-Critic CPG Architecture
- 2013
-
In: Advances in Artificial Life, ECAL 2013, Proceedings of the Twelfth European Conference on the Synthesis and Simulation of Living Systems. - : MIT Press. ; , s. 1182-1190
-
Conference paper (peer-reviewed)abstract
- In this article, a four-cell CPG network, exploiting sensory feedback, is proposed in order to emulate infant crawling gaits when utilized on the NAO robot. Based on the crawling model, the positive episodic natural-actor-critic architecture is applied to learn a proper posture of crawling on a simulated NAO. By transferring the learned results to the physical NAO, the transferability from simulation to physical world is discussed. Finally, a discussion pertaining to locomotion learning based on dynamic system theory is given in the conclusion.
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| 33. |
- Li, Cai, et al.
(author)
-
DMPs based CPG Actor Critic: A Method for Locomotion Learning
- 2014
-
Other publication (other academic/artistic)abstract
- In this article, a dynamic motor primitives (DMPs) based CPG-Actor-Critic is proposed to enable locomotion learning on a humanoid (the NAO robot) and a puppy robot (the ghostdog robot). In order to model two types of locomotion with one architecture, a novel application of an existing method to designa CPG architecture for learning locomotion. The method is to a) have an architectural base (4-cell CPG) and, b) have a learning component which is based on an existing method for designing DMPs. Learning locomotion here concerns gait emergence in relation to the robot’s body and prior knowledge. The focus of this article will be on two types of locomotion: crawling on ahumanoid and running on a puppy robot. On the two robots with two different morphologies, our method and architecture can make the robots learn by itself. We also compare the performance with respect to two state-of-the-art reinforcement learning algorithms with provided particular instantiations of ourDMPs-based CPG-Actor-Critic architecture. Finally, based on the analysis of the experimental results, a generic view/architecture for locomotion learning is discussed and introduced in the conclusion.
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| 34. |
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| 35. |
- Li, Cai, et al.
(author)
-
Humanoids learning to crawl based on Natural CPG-Actor-Critic and Motor Primitives
- 2013
-
In: Proceedings of IROS 2013 Workshop on Neuroscience and Robotics, Tokyo, Japan. ; , s. 7-15
-
Conference paper (other academic/artistic)abstract
- In this article, a new CPG-Actor-Critic architecturebased on motor primitives is proposed to perform a crawlinglearning task on a humanoid (the NAO robot). Starting froman interdisciplinary explanation of the theories, we present twoinvestigations to test the important functions of the layeredCPG architecture: sensory feedback integration and whole-bodyposture control. Based on the analysis of the experimental results,a generic view/architecture for locomotion learning is discussedand introduced in the conclusion.
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| 36. |
- Li, Cai, et al.
(author)
-
Humanoids learning to walk : a natural CPG-actor-critic architecture
- 2013
-
In: Frontiers in Neurorobotics. - : Frontiers Media S.A.. - 1662-5218. ; 7:5
-
Journal article (peer-reviewed)abstract
- The identification of learning mechanisms for locomotion has been the subject of much research for some time but many challenges remain. Dynamic systems theory (DST) offers a novel approach to humanoid learning through environmental interaction. Reinforcement learning (RL) has offered a promising method to adaptively link the dynamic system to the environment it interacts with via a reward-based value system. In this paper, we propose a model that integrates the above perspectives and applies it to the case of a humanoid (NAO) robot learning to walk the ability of which emerges from its value-based interaction with the environment. In the model, a simplified central pattern generator (CPG) architecture inspired by neuroscientific research and DST is integrated with an actor-critic approach to RL (cpg-actor-critic). In the cpg-actor-critic architecture, least-square-temporal-difference based learning converges to the optimal solution quickly by using natural gradient learning and balancing exploration and exploitation. Futhermore, rather than using a traditional (designer-specified) reward it uses a dynamic value function as a stability indicator that adapts to the environment. The results obtained are analyzed using a novel DST-based embodied cognition approach. Learning to walk, from this perspective, is a process of integrating levels of sensorimotor activity and value.
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| 37. |
- Li, Cai, et al.
(author)
-
Humanoids that crawl : Comparing gait performance of iCub and NAO using a CPG architecture
- 2011
-
In: Proceedings - 2011 IEEE International Conference on Computer Science and Automation Engineering, CSAE 2011. - : IEEE conference proceedings. - 9781424487271 - 9781424487288 - 9781424487264 - 9781424487257 ; , s. 577-582
-
Conference paper (peer-reviewed)abstract
- In this article, a generic CPG architecture is used to model infant crawling gaits and is implemented on the NAO robot platform. The CPG architecture is chosen via a systematic approach to designing CPG networks on the basis of group theory and dynamic systems theory. The NAO robot performance is compared to the iCub robot which has a different anatomical structure. Finally, the comparison of performance and NAO whole-body stability are assessed to show the adaptive property of the CPG architecture and the extent of its ability to transfer to different robot morphologies. © 2011 IEEE.
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| 38. |
- Li, Cai, et al.
(author)
-
Modelling Walking Behaviors Based on CPGs : A Simplified Bio-inspired Architecture
- 2012
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In: From Animals to Animats 12. - Berlin; Heidelberg : Springer Berlin/Heidelberg. - 9783642330926 - 9783642330933 ; , s. 156-166
-
Conference paper (peer-reviewed)abstract
- In this article, we use a recurrent neural network including four-cell core architecture to model the walking gait and implement it with the simulated and physical NAO robot. Meanwhile, inspired by the biological CPG models, we propose a simplified CPG model which comprises motorneurons, interneurons, sensor neurons and the simplified spinal cord. Within this model, the CPGs do not directly output trajectories to the servo motors. Instead, they only work to maintain the phase relation among ipsilateral and contralateral limbs. The final output is dependent on the integration of CPG signals, outputs of interneurons, motor neurons and sensor neurons (sensory feedback).
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| 39. |
- Li, Cai
(author)
-
Reinforcement Learning of Locomotion based on Central Pattern Generators
- 2014
-
Doctoral thesis (other academic/artistic)abstract
- Locomotion learning for robotics is an interesting and challenging area in which the movement capabilities of animals have been deeply investigated and acquired knowledge has been transferred into modelling locomotion on robots. What modellers are required to understand is what structure can represent locomotor systems in different animals and how such animals develop various and dexterous locomotion capabilities. Notwithstanding the depth of research in the area, modelling locomotion requires a deep rethinking.In this thesis, based on the umbrella of embodied cognition, a neural-body-environment interaction is emphasised and regarded as the solution to locomotion learning/development. Central pattern generators (CPGs) are introduced in the first part (Chapter 2) to generally interpret the mechanism of locomotor systems in animals. With a deep investigation on the structure of CPGs and inspiration from human infant development, a layered CPG architecture with baseline motion generation and dynamics adaptation interfaces are proposed. In the second part, reinforcement learning (RL) is elucidated as a good method for dealing with locomotion learning from the perspectives of psychology, neuroscience and robotics (Chapter 4). Several continuous-space RL techniques (e.g. episodic natural actor critic, policy learning by weighting explorations with returns, continuous action space learning automaton are introduced for practical use (Chapter 3). With the knowledge of CPGs and RL, the architecture and concept of CPG-Actor-Critic is constructed. Finally, experimental work based on published papers is highlighted in a path of my PhD research (Chapter 5). This includes the implementation of CPGs and the learning on the NAO robot for crawling and walking. The implementation is also extended to test the generalizability to different morphologies (the ghostdog robot). The contribution of this thesis is discussed from two angles: the investigation of the CPG architecture and the implementation (Chapter 6).
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| 40. |
- Liu, Xueping, et al.
(author)
-
Variants in the fetal genome near pro-inflammatory cytokine genes on 2q13 associate with gestational duration.
- 2019
-
In: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 10:1
-
Journal article (peer-reviewed)abstract
- The duration of pregnancy is influenced by fetal and maternal genetic and non-genetic factors. Here we report a fetal genome-wide association meta-analysis of gestational duration, and early preterm, preterm, and postterm birth in 84,689 infants. One locus on chromosome 2q13 is associated with gestational duration; the association is replicated in 9,291 additional infants (combined P=3.96×10-14). Analysis of 15,588 mother-child pairs shows that the association is driven by fetal rather than maternal genotype. Functional experiments show that the lead SNP, rs7594852, alters the binding of the HIC1 transcriptional repressor. Genes at the locus include several interleukin 1 family members with roles in pro-inflammatory pathways that are central to the process of parturition. Further understanding of the underlying mechanisms will be of great public health importance, since giving birth either before or after the window of term gestation is associated with increased morbidity and mortality.
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| 41. |
- Lowe, Robert, et al.
(author)
-
A Dynamic Field Theoretic Model of Iowa Gambling Task Performance
- 2010
-
In: 2010 IEEE 9th International Conference on Development and Learning (ICDL). - : IEEE conference proceedings. - 9781424469024 - 1424469023 - 9781424469000 - 1424469007 ; , s. 297-304
-
Conference paper (peer-reviewed)abstract
- Choice behaviour where outcome-contingencies vary or are prohabilistic has been the focus of many benchmark tasks of infant to adult development in the psychology literature. Dynamic field theoretic (DFT) investigations of cognitive and behavioural competencies have been used in order to identify parameters critical to infant development. In this paper we report the findings of a DFT model that is able to replicate normal functioning adult performance on the Iowa gambling task (IGT). The model offers a simple demonstration proof of the parsimonious reversal learning alternative to Damasio’s somatic marker explanation of IGT performance. Our simple model demonstrates a potentially important role for reinforcement/reward learning to generating behaviour that allows for advantageous performance. We compare our DFT modelling approach to one used on the A-not-B infant paradigm and suggest that a critical aspect of development lies in the ability to flexibly trade off perseverative versus exploratory behaviour in order to capture statistical choice-outcome contingencies. Finally, we discuss the importance of an investigation of the IGT in an embodied setting where reward prediction learning may provide critical means by which adaptive behavioural reversals can be enacted.
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| 42. |
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| 43. |
- Lowe, Robert, et al.
(author)
-
Affective-Associative Two-Process theory: A neural network investigation of adaptive behaviour in differential outcomes training
- 2017
-
In: Adaptive Behavior. - : SAGE Publications. - 1059-7123 .- 1741-2633. ; 25:1, s. 5-23
-
Journal article (peer-reviewed)abstract
- In this article we present a novel neural network implementation of Associative Two-Process (ATP) theory based on an Actor-Critic-like architecture. Our implementation emphasizes the affective components of differential reward magnitude and reward omission expectation and thus we model Affective-Associative Two-Process theory (Aff-ATP). ATP has been used to explain the findings of differential outcomes training (DOT) procedures, which emphasize learning differentially valuated outcomes for cueing actions previously associated with those outcomes. ATP hypothesizes the existence of a prospective' memory route through which outcome expectations can bring to bear on decision making and can even substitute for decision making based on the retrospective' inputs of standard working memory. While DOT procedures are well recognized in the animal learning literature they have not previously been computationally modelled. The model presented in this article helps clarify the role of ATP computationally through the capturing of empirical data based on DOT. Our Aff-ATP model illuminates the different roles that prospective and retrospective memory can have in decision making (combining inputs to action selection functions). In specific cases, the model's prospective route allows for adaptive switching (correct action selection prior to learning) following changes in the stimulus-response-outcome contingencies.
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| 44. |
- Lowe, Robert, et al.
(author)
-
Affective-associative two-process theory: a neurocomputational account of partial reinforcement extinction effects
- 2017
-
In: Biological Cybernetics. - : Springer Science and Business Media LLC. - 0340-1200 .- 1432-0770. ; 111:5-6, s. 365-388
-
Journal article (peer-reviewed)abstract
- The partial reinforcement extinction effect (PREE) is an experimentally established phenomenon: behavioural response to a given stimulus is more persistent when previously inconsistently rewarded than when consistently rewarded. This phenomenon is, however, controversial in animal/human learning theory. Contradictory findings exist regarding when the PREE occurs. One body of research has found a within-subjects PREE, while another has found a within-subjects reversed PREE (RPREE). These opposing findings constitute what is considered the most important problem of PREE for theoreticians to explain. Here, we provide a neurocomputational account of the PREE, which helps to reconcile these seemingly contradictory findings of within-subjects experimental conditions. The performance of our model demonstrates how omission expectancy, learned according to low probability reward, comes to control response choice following discontinuation of reward presentation (extinction). We find that a PREE will occur when multiple responses become controlled by omission expectation in extinction, but not when only one omission-mediated response is available. Our model exploits the affective states of reward acquisition and reward omission expectancy in order to differentially classify stimuli and differentially mediate response choice. We demonstrate that stimulus-response (retrospective) and stimulus-expectation-response (prospective) routes are required to provide a necessary and sufficient explanation of the PREE versus RPREE data and that Omission representation is key for explaining the nonlinear nature of extinction data.
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| 45. |
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| 46. |
- Lowe, Robert, et al.
(author)
-
Bridging Connectionism and Relational Cognition through Bi-directional Affective-Associative Processing
- 2019
-
In: Open Information Science. - : Walter de Gruyter GmbH. - 2451-1781. ; 3:1, s. 235-260
-
Journal article (peer-reviewed)abstract
- Connectionist architectures constitute a popular method for modelling animal associative learning processes in order to glean insights into the formation of cognitive capacities. Such approaches (based on purely feedforward activity) are considered limited in their ability to capture relational cognitive capacities. Pavlovian learning value-based models, being not based purely on fully connected feedforward structure, have demonstrated learning capabilities that often mimic those of ‘higher’ relational cognition. Capturing data using such models often reveals how associative mechanisms can exploit structure in the experimental setting, so that ‘explicit’ relational cognitive capacities are not, in fact, required. On the other hand, models of relational cognition, implemented as neural networks, permit formation and retrieval of relational representations of varying levels of complexity. The flexible processing capacities of such models are, however, are subject to constraints as to how offline relational versus online (real-time, real-world) processing may be mediated. In the current article, we review the potential for building a connectionist-relational cognitive architecture with reference to the representational rank view of cognitive capacity put forward by Halford et al. Through interfacing system 1-like (connectionist/associative learning) and system 2-like (relational-cognition) computations through a bidirectional affective processing approach, continuity between Halford et al’s cognitive systems may be operationalized according to real world/online constraints. By addressing i) and ii) in this manner, this paper puts forward a testable unifying framework for system 1-like and system 2-like cognition.
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| 47. |
- Lowe, Robert, 1975-, et al.
(author)
-
Designing for a Wearable Affective Interface for the NAO Robot : A Study of Emotion Conveyance by Touch
- 2018
-
In: Multimodal Technologies and Interaction. - : M D P I AG. - 2414-4088. ; 2:1
-
Journal article (peer-reviewed)abstract
- We here present results and analysis from a study of affective tactile communication between human and humanoid robot (the NAO robot). In the present work, participants conveyed eight emotions to the NAO via touch. In this study, we sought to understand the potential for using a wearable affective (tactile) interface, or WAffI. The aims of our study were to address the following: (i) how emotions and affective states can be conveyed (encoded) to such a humanoid robot, (ii) what are the effects of dressing the NAO in the WAffI on emotion conveyance and (iii) what is the potential for decoding emotion and affective states. We found that subjects conveyed touch for longer duration and over more locations on the robot when the NAO was dressed with WAffI than when it was not. Our analysis illuminates ways by which affective valence, and separate emotions, might be decoded by a humanoid robot according to the different features of touch: intensity, duration, location, type. Finally, we discuss the types of sensors and their distribution as they may be embedded within the WAffI and that would likely benefit Human-NAO (and Human-Humanoid) interaction along the affective tactile dimension.
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| 48. |
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| 49. |
- Lowe, Robert
(author)
-
Embodiment in Emotional Learning, Decision Making and Behaviour : The ‘What’ and the ‘How’ of Action
- 2014
-
In: Universal Access in Human-Computer Interaction. Aging and Assistive Environments. - Cham : Springer International Publishing Switzerland. - 9783319074450 - 9783319074467 ; , s. 672-679
-
Conference paper (peer-reviewed)abstract
- Connectionist and bio-inspired approaches to the study of emotional learning and decision making often emphasize, or imply, an executive role for the brain whilst paying only lip service to the role of the non-neural body. In this short paper I will discuss approaches to modelling emotions that have attempted to take into account, in one form or another, the role of the body in emotional learning and decision making. More specifically, I will argue that the ‘how’ of behavioural responding and not just the ‘what’ must be factored into any learning algorithm that purports to be emotional. Furthermore, I will refer to research that has utilized abstract artificial environments designed to explore the relevance of how behaviours are carried out with a view to scaling performance to more complex, including human-based, environments.
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| 50. |
- Lowe, Robert
(author)
-
Emotions in Robots: Embodied Interaction in Social and Non-Social Environments
- 2019
-
In: Multimodal Technologies and Interaction. - : MDPI AG. - 2414-4088. ; 3:3, s. 1-4
-
Journal article (peer-reviewed)abstract
- Whether they are considered discrete or dimensional, emotions are ’embodied’ phenomena. The embodied agent does not play a merely passive role in emotion processing. Rather, the body itself, in interaction with its external environment, influences how real/imagined, environmental stimuli are perceived and acted upon. The body behaviorally orients and acts, and internally physiologically ‘prepares’ in relation to its external environment [1]. Today, we see a shift towards robots that need to interact in relation to the social and emotional aspects of human environments. There are at least two areas in which ‘embodied’ implementations of emotional processes can enhance robotic performance in human environments: (i) improved human-inter-actor experience and (ii) facilitated competence. The mode of embodiment of the emotion-guided robot entails not only its physical dimension regarding how and what it senses and appears to human inter-actors, but also its internal homeostatic aspects that regulate its goals and those very same interactions. The increased emphasis over the past two decades in the area of social and non-social robotics on emotional activity is a testimony to its perceived importance within the robotics community. The embodied emotional activity in robots is perhaps most famously recognized in terms of emotion expression capabilities, above all with respect to facial expression [2,3]. The extent to which such robots socially appropriately express emotional or empathic states [3], e.g., according to underlying homeostatic computations [2], largely determines the extent to which the robots are positively received by their human inter-actors. Such aspects of embodiment to emotional activity in robots, including how emotions influence decision-making and aspects of functional (including non-social) interactive behavior, are often undervalued or at least sub-ordinated with respect to the expressive facets of emotional embodiment. The aforementioned role of homeostasis has been demonstrated to provide an important function for robots required to behave autonomously over unspecified durations, e.g., in not-well-understood, or otherwise inaccessible, environments [4,5,6,7,8,9,10]. This notion has more recently been extended to incorporate the notion of predictive regulation (or allostasis) [11,12] and has been considered with respect to artificial systems [13,14]. Providing the tools for robots to not just express but also interpret embodied emotional engagement, e.g., through the modality of tactile interaction [15,16,17], also provides an interesting area of relatively recent research. Robotic agents have also been used in clinical settings, e.g., to facilitate the development of autistic children for whom a robot, more predictable than a human, can provide a suitable interacting partner. The physical appearance, mode of embodied interaction, and environmental setting, all provide crucial elements in the emotional engagement that can ensue [18]. Even outside the clinical setting, robots designed to interact with humans over long periods, i.e., not just as care-givers or trainers, but as robotic companions, should engage with humans in ways that are functional, believable, and even creative [19].
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