This paper proposes a novel global optimization algorithm called Political Optimizer (PO), inspired by the multi-phased process of politics. PO is the mathematical mapping of all the major phases of ...politics such as constituency allocation, party switching, election campaign, inter-party election, and parliamentary affairs. The proposed algorithm assigns each solution a dual role by logically dividing the population into political parties and constituencies, which facilitates each candidate to update its position with respect to the party leader and the constituency winner. Moreover, a novel position updating strategy called recent past-based position updating strategy (RPPUS) is introduced, which is the mathematical modeling of the learning behaviors of the politicians from the previous election. The proposed algorithm is benchmarked with 50 unimodal, multimodal, and fixed dimensional functions against 15 state of the art algorithms. We show through experiments that PO has an excellent convergence speed with good exploration capability in early iterations. Root cause of such behavior of PO is incorporation of RPPUS and logical division of the population to assign dual role to each candidate solution. Using Wilcoxon rank-sum test, PO demonstrates statistically significant performance over the other algorithms. The results show that PO outperforms all other algorithms, and consistency in performance on such a comprehensive suite of benchmark functions proves the versatility of the algorithm. Furthermore, experiments demonstrate that PO is invariant to function shifting and performs consistently in very high dimensional search spaces. Finally, the applicability on real-world applications is demonstrated by efficiently solving four engineering optimization problems.
This text maintains that the presuppositions of individualistic empiricism have been instrumental for the neoliberal revolution, which turns supposed aggressiveness and natural selfishness into a ...foundation of society. The combination of science that denies the relational, emotional and subjective nature of humans with the naturalisation of individualism and competition as supposed bases of human behaviour combine to hinder Action Research's aim of "self-determination" (Fricke, 2018). However, true relational parameters, located in and empathic with the living, fit perfectly with the assumptions of AR. Therefore, we explain how discoveries in biology not only show that the bases of Action Research are not heretical from a scientific point of view, but that they fit in perfectly with the true parameters of behaviour identified by the life sciences. Keywords: Neoliberalism; Biology; Neurology; emotions; science Este texto defiende que los presupuestos del empirismo individualista han sido funcionalespara una revolucion neoliberalque convierte una supuesta agresividad y egoismo natural en fundamento de lo social. La combination de una ciencia que niega el caracter relacional, emocional ysubjetivo con la naturalization del individualismo ylacompetencia como supuestas bases del comportamiento humano se conjuran para dificultar la apuesta de la Action Researh por la "autodeterminacion" de las personas (Fricke, 2018). Sin embargo, los verdaderos parametros relacionales, situados yempaticos de lo vivo encajan alaperfeccion con los presupuestos de la AR. Para ello, explicamos como los descubrimientos en genetica, biologia yneurologia muestran que las bases de la Action Research no solo no hereticas desde un punto de vista cientifico, sino que se ajustan a la perfeccioncon los verdaderos parametros del comportamiento que identifican las ciencias de la vida. Palabras clave: Neoliberalismo; Biologia; neurologia; emociones; ciencia
Learning dexterous in-hand manipulation Andrychowicz, OpenAI: Marcin; Baker, Bowen; Chociej, Maciek ...
The International journal of robotics research,
01/2020, Letnik:
39, Številka:
1
Journal Article
Recenzirano
Odprti dostop
We use reinforcement learning (RL) to learn dexterous in-hand manipulation policies that can perform vision-based object reorientation on a physical Shadow Dexterous Hand. The training is performed ...in a simulated environment in which we randomize many of the physical properties of the system such as friction coefficients and an object’s appearance. Our policies transfer to the physical robot despite being trained entirely in simulation. Our method does not rely on any human demonstrations, but many behaviors found in human manipulation emerge naturally, including finger gaiting, multi-finger coordination, and the controlled use of gravity. Our results were obtained using the same distributed RL system that was used to train OpenAI Five. We also include a video of our results: https://youtu.be/jwSbzNHGflM.
Zipf-like distributions characterize a wide set of phenomena in physics, biology, economics, and social sciences. In human activities, Zipf's law describes, for example, the frequency of appearance ...of words in a text or the purchase types in shopping patterns. In the latter, the uneven distribution of transaction types is bound with the temporal sequences of purchases of individual choices. In this work, we define a framework using a text compression technique on the sequences of credit card purchases to detect ubiquitous patterns of collective behavior. Clustering the consumers by their similarity in purchase sequences, we detect five consumer groups. Remarkably, post checking, individuals in each group are also similar in their age, total expenditure, gender, and the diversity of their social and mobility networks extracted from their mobile phone records. By properly deconstructing transaction data with Zipf-like distributions, this method uncovers sets of significant sequences that reveal insights on collective human behavior.
The Brazilian Journal of Motor Behavior (BJMB) is a quadriannual, peer-reviewed, free of charge/fee and open-access journal published by the Brazilian Society of Motor Behavior (SOCIBRACOM). The BJMB ...has published original contributions within the multidisciplinary study of human motor behavior, in the broad scope of motor control, development and learning, movement disorders, sports, clinical, theoretical and model studies. Since 2019 the BJMBpublishes manuscripts only in English. In the same year, BJMB started to invite researchers to be guest editors in article collections, providing an excellent opportunity to promote high-quality contents within the field.
The BJMB is the main motor behavior journal in the Latin American. It is widely recognized for its significant academic contribution and indexed in the UlrichsWeb Global Serial Directory, Diadorium, Gale Directory Library, Google Scholar, Road Directory of Open Access Scholary resources and Red Iberoamericana de Innovación y Conocimiento Científico. The number of edition and papers has sustainable and significantly increased in the last years, with over 500 authors contributing with 121 manuscripts, distributed in 40 numbers. The time of peer-reviewed process is short (first revision- 26 days) and paper publication is quick (57 days).
The BJMB was launched with its first edition published in December of 2006 and, thus, we are celebrating its 15thanniversary. For that, the BJMB launches a new type of manuscript: INFOGRAPHIC. This initiative aims to provide a quick, easy-to-use and enjoyable publication that conveys notable knowledge. Two types of infographics will be publishable: a) theory perspective: visual material to theory acknowledge to facilitate the understanding of models, theory frameworks, concepts, principles, and approaches in the field; b) article infographic: visual material about interventional effects on motor learning, development and control sustained by reviews and/or meta-analysis.
The infographic section will be added to those already existing: research, systematic review and meta-analysis, mini review, scoping review, research notes, current opinion, critique, and tutorials. It is interesting to highlight the section about tutorial, which emphasizes and provides reflection on the use of one or several methods or self-instruction in motor behavior. Finally, the current opinion section publishes pieces of diverse authors around the world that provide perspectives on a hot, relevant, and perhaps controversial topic within the scope of BJMB.
We would like to congratulate all for this important occasion and to wish that the BJMB continues publishing impactful and relevant contributions in the motor behavior field still for many years to come.
Privacy and human behavior in the age of information Acquisti, Alessandro; Brandimarte, Laura; Loewenstein, George
Science (American Association for the Advancement of Science),
01/2015, Letnik:
347, Številka:
6221
Journal Article
Recenzirano
This Review summarizes and draws connections between diverse streams of empirical research on privacy behavior. We use three themes to connect insights from social and behavioral sciences: people's ...uncertainty about the consequences of privacy-related behaviors and their own preferences over those consequences; the context-dependence of people's concern, or lack thereof, about privacy; and the degree to which privacy concerns are malleable—manipulable by commercial and governmental interests. Organizing our discussion by these themes, we offer observations concerning the role of public policy in the protection of privacy in the information age.
Derived from rapid advances in computer vision and machine learning, video analysis tasks have been moving from inferring the present state to predicting the future state. Vision-based action ...recognition and prediction from videos are such tasks, where action recognition is to infer human actions (present state) based upon complete action executions, and action prediction to predict human actions (future state) based upon incomplete action executions. These two tasks have become particularly prevalent topics recently because of their explosively emerging real-world applications, such as visual surveillance, autonomous driving vehicle, entertainment, and video retrieval, etc. Many attempts have been devoted in the last a few decades in order to build a robust and effective framework for action recognition and prediction. In this paper, we survey the complete state-of-the-art techniques in action recognition and prediction. Existing models, popular algorithms, technical difficulties, popular action databases, evaluation protocols, and promising future directions are also provided with systematic discussions.
•A survey of 736 college students found that Facebook use can trigger feelings of envy.•Feelings of envy were found to predict depression symptoms.•The effect of surveillance use of Facebook on ...depression is mediated by feelings of envy.•Surveillance use of Facebook has a direct link to depression, but the link is actually negative.
It is not—unless it triggers feelings of envy. This study uses the framework of social rank theory of depression and conceptualizes Facebook envy as a possible link between Facebook surveillance use and depression among college students. Using a survey of 736 college students, we found that the effect of surveillance use of Facebook on depression is mediated by Facebook envy. However, when Facebook envy is controlled for, Facebook use actually lessens depression.
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