Foundations of Trusted Autonomy

Trusted Autonomy; Automation Technology; Autonomous Systems; Self-Governance; Trusted Autonomous Systems; Design of Algorithms and Methodologie

Should artificial agents ask for help in human-robot collaborative problem-solving?

International audienceTransferring as fast as possible the functioning of our brain to artificial intelligence is an ambitious goal that would help advance the state of the art in AI and robotics. It is in this perspective that we propose to start from hypotheses derived from an empirical study in a human-robot interaction and to verify if they are validated in the same way for children as for a basic reinforcement learning algorithm. Thus, we check whether receiving help from an expert when solving a simple close-ended task (the Towers of Hanoï) allows to accelerate or not the learning of this task, depending on whether the intervention is canonical or requested by the player. Our experiences have allowed us to conclude that, whether requested or not, a Q-learning algorithm benefits in the same way from expert help as children do

Harnessing the Power of Collective Intelligence: the Case Study of Voxel-based Soft Robots

The field of Evolutionary Robotics (ER) is concerned with the evolution of artificial agents---robots. Albeit groundbreaking, progress in the field has recently stagnated. In the research community, there is a strong feeling that a paradigm change has become necessary to disentangle ER. In particular, a solution has emerged from ideas from Collective Intelligence (CI). In CI---which has many relevant examples in nature---behavior emerges from the interaction between several components. In the absence of central intelligence, collective systems are usually more adaptable. In this thesis, we set out to harness the power of CI, focusing on the case study of simulated Voxel-based Soft Robots (VSRs): they are aggregations of homogeneous and soft cubic blocks that actuate by altering their volume. We investigate two axes. First, the morphologies of VSRs are intrinsically modular and an ideal substrate for CI; nevertheless, controllers employed until now do not take advantage of such modularity. Our results prove that VSRs can truly be controlled by the CI of their modules. Second, we investigate the spatial and time scales of CI. In particular, we evolve a robot to detect its global body properties given only local information processing, and, in a different study, generalize better to unseen environmental conditions through Hebbian learning. We also consider how evolution and learning interact in VSRs. Looking beyond VSRs, we propose a novel soft robot formalism that more closely resembles natural tissues and blends local with global actuation.The field of Evolutionary Robotics (ER) is concerned with the evolution of artificial agents---robots. Albeit groundbreaking, progress in the field has recently stagnated. In the research community, there is a strong feeling that a paradigm change has become necessary to disentangle ER. In particular, a solution has emerged from ideas from Collective Intelligence (CI). In CI---which has many relevant examples in nature---behavior emerges from the interaction between several components. In the absence of central intelligence, collective systems are usually more adaptable. In this thesis, we set out to harness the power of CI, focusing on the case study of simulated Voxel-based Soft Robots (VSRs): they are aggregations of homogeneous and soft cubic blocks that actuate by altering their volume. We investigate two axes. First, the morphologies of VSRs are intrinsically modular and an ideal substrate for CI; nevertheless, controllers employed until now do not take advantage of such modularity. Our results prove that VSRs can truly be controlled by the CI of their modules. Second, we investigate the spatial and time scales of CI. In particular, we evolve a robot to detect its global body properties given only local information processing, and, in a different study, generalize better to unseen environmental conditions through Hebbian learning. We also consider how evolution and learning interact in VSRs. Looking beyond VSRs, we propose a novel soft robot formalism that more closely resembles natural tissues and blends local with global actuation

Development and testing of a novel dimensional framework for understanding human attachment

Attachment is the deep emotional bond that every human being needs to create with another. In the prototypical case, the child attaches to their mother. In this work, I present the Attachment-Personality Theory (APT), which proposes an enhancement of the Standard Attachment Theory (SAT) from a cognitive-clinical perspective. By focusing on the representational and dimensional nature of attachment, the APT suggests that attachment knowledge is based on seven dimensions, which constitute the core of personality. Accordingly, I outline an attachment module that functions as a seven-dimensional control system. I empirically test the APT through (1) the Attachment-Caregiving Questionnaire (ACQ) – a clinical self-report that works as a personality inventory – and (2) the Attachment Computational Model (ACM) – an agent-based model of three attachment dimensions. The analysis of the ACQ administered on a small sample provides preliminary support to the APT and encourages using artificial pattern recognition for further analysis. The ACM generates results compliant with the theory. Overall, this research suggests that the APT might contribute to bridging the gap between clinical psychology and engineering, favoring applications closer to psychological data. Moreover, independently of the APT, the developed clinical questionnaire and computational model can provide insights into attachment nature and novel methodological directions in synthetic psychology

Our Mythical Hope

Classical Antiquity is a particularly important field in terms of “Hope studies” […]. For centuries, the ancient tradition, and classical mythology in particular, has been a common reference point for whole hosts of creators of culture, across many parts of the world, and with the new media and globalization only increasing its impact. Thus, in our research at this stage, we have decided to study how the authors of literary and audiovisual texts for youth make use of the ancient myths to support their young protagonists (and readers or viewers) in crucial moments of their existence, on their road into adulthood, and in those dark hours when it seems that life is about to shatter and fade away. However, if Hope is summoned in time, the crisis can be overcome and the protagonist grows stronger, with a powerful uplifting message for the public. […] Owing to this, we get a chance to remain true to our ideas, to keep faith in our dreams, and, when the decisive moment comes, to choose not hatred but love, not darkness but light. Katarzyna Marciniak, University of Warsaw, From the introductory chapte

Our Mythical Hope

Classical Antiquity is a particularly important field in terms of “Hope studies” […]. For centuries, the ancient tradition, and classical mythology in particular, has been a common reference point for whole hosts of creators of culture, across many parts of the world, and with the new media and globalization only increasing its impact. Thus, in our research at this stage, we have decided to study how the authors of literary and audiovisual texts for youth make use of the ancient myths to support their young protagonists (and readers or viewers) in crucial moments of their existence, on their road into adulthood, and in those dark hours when it seems that life is about to shatter and fade away. However, if Hope is summoned in time, the crisis can be overcome and the protagonist grows stronger, with a powerful uplifting message for the public. […] Owing to this, we get a chance to remain true to our ideas, to keep faith in our dreams, and, when the decisive moment comes, to choose not hatred but love, not darkness but light. Katarzyna Marciniak, University of Warsaw, From the introductory chapte