Neurally Plausible Model of Robot Reaching Inspired by Infant Motor Babbling

In this dissertation, we present an abstract model of infant reaching that is neurally-plausible. This model is grounded in embodied artificial intelligence, which emphasizes the importance of the sensorimotor interaction of an agent and the world. It includes both learning sensorimotor correlations through motor babbling and also arm motion planning using spreading activation. We introduce a mechanism called bundle formation as a way to generalize motions during the motor babbling stage. We then offer a neural model for the abstract model, which is composed of three layers of neural maps with parallel structures representing the same sensorimotor space. The motor babbling period shapes the structure of the three neural maps as well as the connections within and between them; these connections encode trajectory bundles in the neural maps. We then investigate an implementation of the neural model using a reaching task on a humanoid robot. Through a set of experiments, we were able to find the best way to implement different components of this model such as motor babbling, neural representation of sensorimotor space, dimension reduction, path planning, and path execution. After the proper implementation had been found, we conducted another set of experiments to analyze the model and evaluate the planned motions. We evaluated unseen reaching motions using jerk, end effector error, and overshooting. In these experiments, we studied the effect of different dimensionalities of the reduced sensorimotor space, different bundle widths, and different bundle structures on the quality of arm motions. We hypothesized a larger bundle width would allow the model to generalize better. The results confirmed that the larger bundles lead to a smaller error of end-effector position for testing targets. An experiment with the resolution of neural maps showed that a neural map with a coarse resolution produces less smooth motions compared to a neural map with a fine resolution. We also compared the unseen reaching motions under different dimensionalities of the reduced sensorimotor space. The results showed that a smaller dimension leads to less smooth and accurate movements

A minimalist approach to deep multi-task learning

Multi-task learning is critical for real-life applications of machine learning. Modern approaches are characterised by algorithmic complexity, often unjustified, leading to impractical solutions. In contrast, this thesis demonstrates that a minimalistic alternative is possible, showing the attractiveness of simple methods. 'In defence of the Unitary Scalarisation for Deep Multi-task Learning' motivates the rest of the thesis, showing that none of the more complex multi-task optimisers outperforms the simple per-task gradient summation when compared on fair grounds. Furthermore, it proposes a novel look at multi-task optimisers from the regularisation standpoint. The rest of this thesis focuses on deep reinforcement learning, a general framework for sequential decision-making. In particular, we look at the setting when observations (inputs to the model) are represented as graphs, i.e., collections of interconnected nodes. In 'Scaling GNNs to High-Dimensional Continuous Control' and 'The Role of Morphology in Graph-Based Incompatible Control', we learn a single control policy for agents of different morphology by representing the observation set elements as graphs and deploy graph neural networks (including transformers). In the former chapter, we devise a simple method to scale graph networks by freezing some parts of the network to stabilise learning and prevent overfitting. In the latter chapter, we show that graph connectivity might be suboptimal for the downstream task demonstrating that less-constrained transformers perform significantly better without having the graph connectivity information. Finally, in the 'Generalisable Branching Heuristic for a SAT Solver', we apply multi-task reinforcement learning to Boolean satisfiability, a fundamental problem in academia and industrial applications. We demonstrate that Q-learning, a staple reinforcement learning algorithm equipped with graph neural networks for function approximation, can learn a generalisable branching heuristic. We hope our findings will steer the further development of the field: creating more complex benchmarks, adding assumptions on task similarities and a model capacity, and exploring other objective functions rather than focusing on the average performance across the tasks

Conference on Intelligent Robotics in Field, Factory, Service, and Space (CIRFFSS 1994), volume 1

The AIAA/NASA Conference on Intelligent Robotics in Field, Factory, Service, and Space (CIRFFSS '94) was originally proposed because of the strong belief that America's problems of global economic competitiveness and job creation and preservation can partly be solved by the use of intelligent robotics, which are also required for human space exploration missions. Individual sessions addressed nuclear industry, agile manufacturing, security/building monitoring, on-orbit applications, vision and sensing technologies, situated control and low-level control, robotic systems architecture, environmental restoration and waste management, robotic remanufacturing, and healthcare applications

New Flesh Cinema: Japanese Cyberpunk-Body Horror and Cinema as Catharsis in the Age of Technology

This thesis provides a critical analysis of a specific group of films that combine the subgenres of cyberpunk and body horror which I call New Flesh Cinema. Films of this subgenre counter fears and anxieties of technological advancements by re-imagining the rise of technology and its societal effects as a transitional process through the illustration of literal and visceral depictions of the necessary alterations people will have to undergo in order to transition successfully into the new world. To contradict apocalyptic fears of advancing technology, these films offer a vision of a “New Flesh.” I argue the films share three important commonalities: they depict technology as a mediator of our actions, interactions, and perception of reality, they stress the importance and discomfort of adapting and transforming, and they address technophobia by revealing a fascination and fear of technology as well as the need and inevitability of a new flesh for a new world. The analysis develops over three case studies of five New Flesh Cinema films: Katsuhiro Otomo’s Akira (1988), Shinya Tsukamoto’s Tetsuo: The Iron Man (1989), Shigeru Izumiya’s Death Powder (1986), Shozin Fukui’s 964 Pinocchio (1991), and Fukui’s Rubber’s Lover (1996). Through these case studies, I shed light on the social significance of New Flesh Cinema as a cathartic medium for an anxious society facing social changes. This contributes to a larger conversation concerning media and society’s cyclical pattern of influence. NB: A note on Japanese titles, terms, and names. If the title of a film varies from its English translation, I provide a Romanized version of the original title in parentheses. Japanese terms are italicized with their English translation in parentheses. Names are given in the following order: given name first, family name second

Extimate Technology

"This book investigates how we should form ourselves in a world saturated with technologies that are profoundly intruding in the very fabric of our selfhood.　 New and emerging technologies, such as smart technological environments, imaging technologies and smart drugs, are increasingly shaping who and what we are and influencing who we ought to be. How should we adequately understand, evaluate and appreciate this development? Tackling this question requires going beyond the persistent and stubborn inside-outside dualism and recognizing that what we consider our ""inside"" self is to a great extent shaped by our ""outside"" world. Inspired by various philosophers – especially Nietzsche, Peirce and Lacan –this book shows how the values, goals and ideals that humans encounter in their environments not only shape their identities but also enable them to critically relate to their present state. The author argues against understanding technological self-formation in terms of making ourselves better, stronger and smarter. Rather, we should conceive it in terms of technological sublimation, which redefines the very notion of human enhancement. In this respect the author introduces an alternative, more suitable theory, namely Technological Sublimation Theory (TST). Extimate Technology will be of interest to scholars and advanced students working in philosophy of technology, philosophy of the self, phenomenology, pragmatism, and history of philosophy.

Extimate Technology

"This book investigates how we should form ourselves in a world saturated with technologies that are profoundly intruding in the very fabric of our selfhood.　 New and emerging technologies, such as smart technological environments, imaging technologies and smart drugs, are increasingly shaping who and what we are and influencing who we ought to be. How should we adequately understand, evaluate and appreciate this development? Tackling this question requires going beyond the persistent and stubborn inside-outside dualism and recognizing that what we consider our ""inside"" self is to a great extent shaped by our ""outside"" world. Inspired by various philosophers – especially Nietzsche, Peirce and Lacan –this book shows how the values, goals and ideals that humans encounter in their environments not only shape their identities but also enable them to critically relate to their present state. The author argues against understanding technological self-formation in terms of making ourselves better, stronger and smarter. Rather, we should conceive it in terms of technological sublimation, which redefines the very notion of human enhancement. In this respect the author introduces an alternative, more suitable theory, namely Technological Sublimation Theory (TST). Extimate Technology will be of interest to scholars and advanced students working in philosophy of technology, philosophy of the self, phenomenology, pragmatism, and history of philosophy.

A vision-based optical character recognition system for real-time identification of tractors in a port container terminal

Automation has been seen as a promising solution to increase the productivity of modern sea port container terminals. The potential of increase in throughput, work efficiency and reduction of labor cost have lured stick holders to strive for the introduction of automation in the overall terminal operation. A specific container handling process that is readily amenable to automation is the deployment and control of gantry cranes in the container yard of a container terminal where typical operations of truck identification, loading and unloading containers, and job management are primarily performed manually in a typical terminal. To facilitate the overall automation of the gantry crane operation, we devised an approach for the real-time identification of tractors through the recognition of the corresponding number plates that are located on top of the tractor cabin. With this crucial piece of information, remote or automated yard operations can then be performed. A machine vision-based system is introduced whereby these number plates are read and identified in real-time while the tractors are operating in the terminal. In this paper, we present the design and implementation of the system and highlight the major difficulties encountered including the recognition of character information printed on the number plates due to poor image integrity. Working solutions are proposed to address these problems which are incorporated in the overall identification system.postprin