1,720,956 research outputs found
Constraint-Procedural Logic Generated Environments for Deep Q-learning Agent training and benchmarking
Full text linkWhile training and benchmarking neural networks, a large and precise set of data and an efficient test environment are parts of a successful process. A good data set is usually produced with high effort in terms of cost and human work to satisfy the constraints imposed by the expected results. In the first part of this paper we focus on the specification of the properties of the solutions needed to build a data set rather than using common primitives of imperative programming, exploring the possibility to procedurally generate data-sets using constraint programming in Prolog. In this phase geometric predicates describe a virtual environment according to inter-space requirements. The second part is focused to test the generated data set in a machine learning context by means of an AI gym and space search techniques. We developed a deep Q-learning model based neural network agent in Python able to address the NP search problem in the virtual space; the agent has the goal to explore the generated virtual environment to seek for a target, improving its performance through a reinforced learning process. © 2022 Copyright for this paper by its authors
Multi-agent system engineering for emphatic human-robot interaction
No full textHuman-robot interactions have to take into account the natural multi-modal bidirectional communication model that is common among humans. The model does not rely just on speech and verbal exchange, but it shall include emotional exchange through different channels: face muscles, body posture, voice modulation, skin responses, odors, etc. While some aspects are feasible yet far from being adopted by daily robotic interaction with humans, the other ones can exploit current level of technology so as to be included in common, although complex, human-robot communication use cases. In order to cope in synergic but efficient and modular way with the various emphatic communication aspects, we propose to employ intelligent agents and multi-agent system. Such multi-agent system comprises a controller sub-system aboard the robot, which is coordinated by logical agents that can incorporate perceptive modules which generates state predicates, reason about them, plan, and deliver emotionally intelligent action while interacting with human beings, emulating as much as possible human empathy
Systematic review on privacy categorisation
Full text linkIn the modern digital world users need to make privacy and security choices that have far-reaching consequences. Researchers are increasingly studying people's decisions when facing with privacy and security trade-offs, the pressing and time consuming disincentives that influence those decisions, and methods to mitigate them. This work aims to present a systematic review of the literature on privacy categorisation, which has been defined in terms of profile, profiling, segmentation, clustering and personae. Privacy categorisation involves the possibility to classify users according to specific prerequisites, such as their ability to manage privacy issues, or in terms of which type of and how many personal information they decide or do not decide to disclose. Privacy categorisation has been defined and used for different purposes. The systematic review focuses on three main research questions that investigate the study contexts, i.e. the motivations and research questions, that propose privacy categorisations; the methodologies and results of privacy categorisations; the evolution of privacy categorisations over time. Ultimately it tries to provide an answer whether privacy categorisation as a research attempt is still meaningful and may have a future. & COPY; 2023 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
SkRobot: a pseudo-realtime multiplatform framework for robotics agents development
Full text linkSkRobot is a software platform that simplifies robot development, especially for those with cognitive capabilities. It uses the C++ SpecialK framework as its foundation. It provides active data brokering, distributed storage and processing, and pseudo-realtime synchronisation, enabling efficient communication between system entities. The platform relies on FlowProtocol, a custom protocol that ensures robust binary communication over network channels. SkRobot’s architecture is designed for simplicity and efficiency, allowing developers to focus on functions while reducing the influence of system artefacts. This framework enables developers to quickly understand robotic paradigms, including cognitive robotics, and meet various implementation needs efficiently
Extension of constraint-procedural logic-generated environments for deep Q-learning agent training and benchmarking
No full textAutonomous robots can be employed in exploring unknown environments and performing many tasks, such as, e.g. detecting areas of interest, collecting target objects, etc. Deep reinforcement learning (RL) is often used to train this kind of robot. However, concerning the artificial environments aimed at testing the robot, there is a lack of available data sets and a long time is needed to create them from scratch. A good data set is in fact usually produced with high effort in terms of cost and human work to satisfy the constraints imposed by the expected results. In the first part of this paper, we focus on the specification of the properties of the solutions needed to build a data set, making the case of environment exploration. In the proposed approach, rather than using imperative programming, we explore the possibility of generating data sets using constraint programming in Prolog. In this phase, geometric predicates describe a virtual environment according to inter-space requirements. The second part of the paper is focused on testing the generated data set in an AI gym via space search techniques. We developed a Neuro-Symbolic agent built from the following: (i) A deep Q-learning component implemented in Python, able to address via RL a search problem in the virtual space; the agent has the goal to explore a generated virtual environment to seek for a target, improving its performance through a RL process. (ii) A symbolic component able to re-address the search when the Q-learning component gets stuck in a part of the virtual environment; these components stimulate the agent to move to and explore other parts of the environment. Wide experimentation has been performed, with promising results, and is reported, to demonstrate the effectiveness of the approach
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe 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
Full text link“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
Full text linkWe 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
Full text linkWe 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
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