1,721,229 research outputs found
An experimental comparison of evolved neural network models for controlling simulated modular soft robots
Get PDFVoxel-based soft robots (VSRs) are a type of modular robots composed by interconnected soft and deformable blocks, i.e., voxels. Thanks to the softness of their bodies, VSRs may exhibit rich dynamic behaviors. One open question is what type of neural controller is most suitable for a given morphology and sensory apparatus in a given environment. One observation is that artificial neural networks with state may be able to cope with the dynamical nature of VSR bodies and their morphological computation. In this work, we consider four types of controllers, i.e., multilayer perceptrons (MLPs, stateless), recurrent neural networks (RNNs), spiking neural networks (SNNs) without homeostasis, and SNNs with homeostasis. We consider three robot morphologies tested for locomotion, where each morphology is investigated in simulation with three different types and number of sensors. Neural network controllers are optimized with neuroevolution, and the experimental results are compared in terms of effectiveness, efficiency, and generalization ability. In addition, we analyze the resulting behavior of the robots systematically. Our results show that RNNs are typically more effective while MLPs are often the weakest controllers, particularly for robots with few sensors. However, SNNs are more capable in terms of generalization and the mechanism of homeostasis is often beneficial. Finally, we show that RNNs and SNNs with homeostasis produce a more wide variety of behaviors.publishedVersio
Collective control of modular soft robots via embodied Spiking Neural Cellular Automata
Get PDFVoxel-based Soft Robots (VSRs) are a form of modular soft robots, composed of several deformable cubes, i.e., voxels. Each VSR is thus an ensemble of simple agents, namely the voxels, which must cooperate to give rise to the overall VSR behavior. Within this paradigm, collective intelligence plays a key role in enabling the emerge of coordination, as each voxel is independently controlled, exploiting only the local sensory information together with some knowledge passed from its direct neighbors (distributed or collective control). In this work, we propose a novel form of collective control, influenced by Neural Cellular Automata (NCA) and based on the bio-inspired Spiking Neural Networks: the embodied Spiking NCA (SNCA). We experiment with different variants of SNCA, and find them to be competitive with the state-of-the-art distributed controllers for the task of locomotion. In addition, our findings show significant improvement with respect to the baseline in terms of adaptability to unforeseen environmental changes, which could be a determining factor for physical practicability of VSRs
Optimization of dynamical systems towards criticality and intelligent behavior
Get PDFWith the progress of computing power, artificial intelligence (AI) systems are able to achieve outstanding results that surpass human-level performance on some tasks, such as image recognition. Mainstream AI systems are only able to learn one or more specific tasks, and they commonly fail to go beyond what they were trained for. To have a real breakthrough in the field of AI, those systems require adaptability and the capacity to learn general tasks and data distributions. Such characteristics are among the objectives of artificial general intelligence (AGI) research. The inspiration from biology, neuroscience, and complex systems may guide the development of AGI because AI systems are still rigid instead of self-organizing. Therefore, the research reported in this thesis aims at intelligent dynamical systems that resemble the brain, such as the brain’s critical behavior that may allow the cortex to self-organize to criticality in order to increase computational capacity. The plan to accomplishsuch systems encompasses the usage of optimization methods to find adequate interactions of the components in a complex system, how they are connected with each other, and how they adapt those interactions and connections overtime. The dynamical systems investigated in this research are cellular automata, Boolean networks, and recurrent neural networks with abstract neuron models or with more biologically plausible ones (spiking neurons). Themain optimization method applied in these systems is evolutionary computa-tion or artificial evolution. There are three parts in the presented research. Thefirst uses a deep neural network library to evolve dynamical systems towardscriticality. The second part works on the complexification of spiking neuralnetworks with adaptive synapses for solving tasks in mutable environments.The last one involves the application of neural cellular automata for control-ling robots and even developing their morphology with artificial embryogeny.The results of this research attempt to address some unanswered questionsrelated to the practicality, methodology, and benefits of applying dynamicalsystems in AI
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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