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ARW 2015 Austrian Robotics Workshop
ARW 2015 Austrian Robotics Workshop Proceedings Austrian Robotics Workshop 2015 ARW 2015 hosted by Institute of Networked and Embedded Systems http://nes.aau.at Alpen-Adria Universität Klagenfurt Welcome to ARW 2015! NES has organized and hosted the Austrian Robotics Workshop (ARW) 2015 on May 7-8 in Klagenfurt. With more than 80 participants and speakers from eight dif- ferent countries this workshop grew into an international event where people from academia and industry meet - botics. Two keynote speakers gave inspiring talks on their thrilling research in robotics. Sabine Hauert from Bristol Robotics Laboratory and University of Bristol explained the development of nano-robots and how they may sup- port medical treatment. Werner Huber from BMW Group Research and Technology presented the self-driving cars, which have received a lot of media coverage lately. In addition, participants from industry and academia pre- sented and demonstrated their demos and posters during an interesting joint session. We have invited people to observe live demonstrations and discuss recent advan- cements face to face. NES members also demonstrated the SINUS project and its achievements in autonomous multi-UAV mission, communication architecture, collision avoidance, path planning, and video streaming. The Austrian Robotics Workshop 2016 will take place in Wels. Hope to see you there! Christian Bettstetter, Torsten Andre, Bernhard Rinner, Saeed Yahyanejad ARW 2015 Austrian Robotics Workshop We warmly acknowledge the support of our sponsors: Committees, -
Determinants of Public Cooperation in Multiplex Networks
PAPER • OPEN ACCESS Related content - Leveraging statistical physics to improve Determinants of public cooperation in multiplex understanding of cooperation in multiplex networks networks Feng Fu and Xingru Chen - The evolution of altruism in spatial threshold public goods games via an To cite this article: Federico Battiston et al 2017 New J. Phys. 19 073017 insurance mechanism Jianlei Zhang and Chunyan Zhang - High-performance parallel computing in the classroom using the public goods game as an example View the article online for updates and enhancements. Matjaž Perc Recent citations - Strategy equilibrium in dilemma games with off-diagonal payoff perturbations Marco A. Amaral and Marco A. Javarone - Networks beyond pairwise interactions: Structure and dynamics Federico Battiston et al - Evolution of cooperation in a conformity- driven evolving dynamic social network Zhihu Yang et al This content was downloaded from IP address 151.97.200.161 on 25/06/2020 at 13:52 New J. Phys. 19 (2017) 073017 https://doi.org/10.1088/1367-2630/aa6ea1 PAPER Determinants of public cooperation in multiplex networks OPEN ACCESS Federico Battiston1, Matjaž Perc2,3 and Vito Latora1,4 RECEIVED 1 School of Mathematical Sciences, Queen Mary University of London, London E1 4NS, United Kingdom 21 March 2017 2 Faculty of Natural Sciences and Mathematics, University of Maribor, Koroška cesta 160, SI-2000 Maribor, Slovenia REVISED 3 CAMTP—Center for Applied Mathematics and Theoretical Physics, University of Maribor, Mladinska 3, SI-2000 Maribor, Slovenia 18 April 2017 4 Dipartimento di Fisica ed Astronomia, Università di Catania and INFN, I-95123 Catania, Italy ACCEPTED FOR PUBLICATION 21 April 2017 E-mail: [email protected] PUBLISHED Keywords: public goods game, public cooperation, evolutionary game theory, multiplex networks, multilayer networks 12 July 2017 Original content from this work may be used under Abstract the terms of the Creative fi Commons Attribution 3.0 Synergies between evolutionary game theory and statistical physics have signi cantly improved our licence. -
Arxiv:1306.2296V2 [Physics.Soc-Ph] 28 Jun 2013 Eet Uulcoeainyed H Reward the Yields Cooperation Mutual Defect
Collective behavior and evolutionary games – An introduction MatjaˇzPerc1, ∗ and Paolo Grigolini2, † 1Faculty of Natural Sciences and Mathematics, University of Maribor, Koroˇska cesta 160, SI-2000 Maribor, Slovenia 2Center for Nonlinear Science, University of North Texas, P.O. Box 311427, Denton, Texas 76203-1427, USA This is an introduction to the special issue titled “Collec- In the prisoner’s dilemma game defectors dominate coop- tive behavior and evolutionary games” that is in the making erators, so that in well-mixed populations natural selection at Chaos, Solitons & Fractals. The term collective behavior always favors the former. In the snowdrift game [19], on covers many different phenomena in nature and society. From the other hand, a coexistence of cooperators and defectors is bird flocks and fish swarms to social movements and herding possible even under well-mixed conditions, and spatial struc- effects [1–5], it is the lack of a central planner that makes the ture may even hinder the evolution of cooperation [20]. The spontaneous emergence of sometimes beautifully ordered and prisoner’s dilemma is in fact the most stringent cooperative seemingly meticulously designed behavior all the more sensa- dilemma, where for cooperation to arise a mechanism for the tional and intriguing. The goal of the special issue is to attract evolution of cooperation is needed [21]. This leads us to the submissions that identify unifying principles that describe the year 1992, when Nowak and May [22] observed the sponta- essential aspects of collective behavior, and which thus allow neous formation of cooperative clusters on a square lattice, for a better interpretation and foster the understanding of the which enabled cooperators to survive in the presence of de- complexity arising in such systems. -
The Power and Promise of Computers That Learn by Example
Machine learning: the power and promise of computers that learn by example MACHINE LEARNING: THE POWER AND PROMISE OF COMPUTERS THAT LEARN BY EXAMPLE 1 Machine learning: the power and promise of computers that learn by example Issued: April 2017 DES4702 ISBN: 978-1-78252-259-1 The text of this work is licensed under the terms of the Creative Commons Attribution License which permits unrestricted use, provided the original author and source are credited. The license is available at: creativecommons.org/licenses/by/4.0 Images are not covered by this license. This report can be viewed online at royalsociety.org/machine-learning Cover image © shulz. 2 MACHINE LEARNING: THE POWER AND PROMISE OF COMPUTERS THAT LEARN BY EXAMPLE Contents Executive summary 5 Recommendations 8 Chapter one – Machine learning 15 1.1 Systems that learn from data 16 1.2 The Royal Society’s machine learning project 18 1.3 What is machine learning? 19 1.4 Machine learning in daily life 21 1.5 Machine learning, statistics, data science, robotics, and AI 24 1.6 Origins and evolution of machine learning 25 1.7 Canonical problems in machine learning 29 Chapter two – Emerging applications of machine learning 33 2.1 Potential near-term applications in the public and private sectors 34 2.2 Machine learning in research 41 2.3 Increasing the UK’s absorptive capacity for machine learning 45 Chapter three – Extracting value from data 47 3.1 Machine learning helps extract value from ‘big data’ 48 3.2 Creating a data environment to support machine learning 49 3.3 Extending the lifecycle -
An Abstract of the Dissertation Of
AN ABSTRACT OF THE DISSERTATION OF Karina A. Roundtree for the degree of Doctor of Philosophy in Mechanical Engineering presented on August 21, 2020. Title: Achieving Transparency in Human-Collective Systems Abstract approved: H. Onan Demirel Julie A. Adams Collective robotic systems are biologically-inspired and exhibit behaviors found in spa- tial swarms (e.g., fish), colonies (e.g., ants), or a combination of both (e.g., bees). Collec- tive robotic system popularity continues to increase due to their apparent global intel- ligence and emergent behaviors. Many applications can benefit from the incorporation of collectives, including environmental monitoring, disaster response missions, and in- frastructure support. Human-collective system designers continue to debate how best to achieve transparency in human-collective systems in order to attain meaningful and insightful information exchanges between the operator and collective, enable positive operator influence on collectives, and improve the human-collective’s performance. Few human-collective evaluations have been conducted, many of which have only assessed how embedding transparency into one system design element (e.g., models, visualizations, or control mechanisms) may impact human-collective behaviors, such as the human-collective performance. This dissertation developed a transparency defi- nition for collective systems that was leveraged to assess how to achieve transparency in a single human-collective system. Multiple models and visualizations were evalu- ated for a sequential best-of-n decision-making task with four collectives. Transparency was evaluated with respect to how the model and visualization impacted human oper- ators who possess different capabilities, operator comprehension, system usability, and human-collective performance. Transparency design guidance was created in order to aid the design of future human-collective systems. -
The Perceived Ethics of Artificial Intelligence
Markets, Globalization & Development Review Volume 5 Number 2 Article 3 2020 The Perceived Ethics of Artificial Intelligence Ross Murray University of Texas Rio Grande Valley Follow this and additional works at: https://digitalcommons.uri.edu/mgdr Part of the Business Law, Public Responsibility, and Ethics Commons, Economics Commons, Marketing Commons, Other Business Commons, Science and Technology Studies Commons, and the Sociology Commons Recommended Citation Murray, Ross (2020) "The Perceived Ethics of Artificial Intelligence," Markets, Globalization & Development Review: Vol. 5: No. 2, Article 3. DOI: 10.23860/MGDR-2020-05-02-03 Available at: https://digitalcommons.uri.edu/mgdr/vol5/iss2/3https://digitalcommons.uri.edu/mgdr/vol5/ iss2/3 This Article is brought to you for free and open access by DigitalCommons@URI. It has been accepted for inclusion in Markets, Globalization & Development Review by an authorized editor of DigitalCommons@URI. For more information, please contact [email protected]. The Perceived Ethics of Artificial Intelligence This article is available in Markets, Globalization & Development Review: https://digitalcommons.uri.edu/mgdr/vol5/ iss2/3 Murray: Ethics of Artificial Intelligence The Perceived Ethics of Artificial Intelligence Introduction Artificial Intelligence (AI) has been embedded in consumer products and services in thousands of products such as Apple’s iPhone, Amazon’s Alexa, Tesla’s autonomous vehicles, Facebook’s algorithms that attempt to increase click-through optimization, and smart vacuum cleaners. As products and services attempt to imitate the intelligence of humans – although the products and services are not making decisions based upon their own moral values – the moral values of the employees and business ethics of corporations that create the products and services are being coded into the technology that is evidenced in these products. -
Hunt, E. R., & Hauert, S. (2020). a Checklist for Safe Robot Swarms. Nature Machine Intelligence
Hunt, E. R. , & Hauert, S. (2020). A checklist for safe robot swarms. Nature Machine Intelligence. https://doi.org/10.1038/s42256-020- 0213-2 Peer reviewed version Link to published version (if available): 10.1038/s42256-020-0213-2 Link to publication record in Explore Bristol Research PDF-document This is the author accepted manuscript (AAM). The final published version (version of record) is available online via Nature Research at https://www.nature.com/articles/s42256-020-0213-2 . Please refer to any applicable terms of use of the publisher. University of Bristol - Explore Bristol Research General rights This document is made available in accordance with publisher policies. Please cite only the published version using the reference above. Full terms of use are available: http://www.bristol.ac.uk/red/research-policy/pure/user-guides/ebr-terms/ 1 A checklist for safe robot swarms 2 3 Edmund Hunt and Sabine Hauert* 4 Engineering Mathematics, Bristol Robotics Laboratory, University of Bristol 5 6 *corresponding author: [email protected] 7 8 Standfirst: As robot swarms move from the laboratory to real world applications, a routine 9 checklist of questions could help ensure their safe operation. 10 11 Robot swarms promise to tackle problems ranging from food production and natural 12 disaster response, to logistics and space exploration1–4. As swarms are deployed outside the 13 laboratory in real world applications, we have a unique opportunity to engineer them to be 14 safe from the get-go. Safe for the public, safe for the environment, and indeed, safe for 15 themselves. -
Britain in the 2020S
REPORT FUTURE PROOF BRITAIN IN THE 2020S Mathew Lawrence December 2016 © IPPR 2016 Institute for Public Policy Research INTRODUCTION Brexit is the firing gun on a decade of disruption. As the UK negotiates its new place in the world, an accelerating wave of economic, social and technological change will reshape the country, in often quite radical ways. In this report, we set out five powerful trends that will drive change in the 2020s. 1. A demographic tipping point: As the population grows, the UK is set to age sharply and become increasingly diverse. Globally, the long expansion of the working-age CONTENTS population is set to slow sharply. 2. An economic world transformed: The economic world order will become more Introduction ............................................................................................................ 3 fragile as globalisation evolves, trade patterns shift, and economic power gravitates toward Asia. At the same time, developed economies are likely to struggle to escape Executive summary: The UK in 2030 ..................................................................... 4 conditions of secular stagnation. The institutions governing the global economy are A world transformed: Five major disruptive forces reshaping Britain .................. 6 likely to come under intense pressure as the American hegemony that underpinned the postwar international order fades and the Global South rises in economic and Britain at the periphery? ..................................................................................8 -
Doubly Effects of Information Sharing on Interdependent Network Reciprocity
New J. Phys. 20 (2018) 075005 https://doi.org/10.1088/1367-2630/aad140 PAPER Doubly effects of information sharing on interdependent network OPEN ACCESS reciprocity RECEIVED 31 May 2018 Chengyi Xia1,2, Xiaopeng Li1,2, Zhen Wang3 and Matjaž Perc4,5,6 REVISED 1 Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology, Tianjin University of Technology, Tianjin 300384, 2 July 2018 Peopleʼs Republic of China ACCEPTED FOR PUBLICATION 2 Key Laboratory of Computer Vision and System (Ministry of Education), Tianjin University of Technology, Tianjin 300384, Peopleʼs 5 July 2018 Republic of China PUBLISHED 3 School of Mechanical Engineering and Center for OPTical IMagery Analysis and Learning (OPTIMAL), Northwestern Polytechnical 17 July 2018 University, Xi’an 710072, Peopleʼs Republic of China 4 Faculty of Natural Sciences and Mathematics, University of Maribor, Koroška cesta 160, SI-2000 Maribor, Slovenia Original content from this 5 CAMTP—Center for Applied Mathematics and Theoretical Physics, University of Maribor, Mladinska 3, SI-2000 Maribor, Slovenia work may be used under 6 School of Electronic and Information Engineering, Beihang University, Beijing 100191, Peopleʼs Republic of China the terms of the Creative Commons Attribution 3.0 E-mail: [email protected] and [email protected] licence. Any further distribution of Keywords: cooperation, evolutionary games, Monte Carlo method, multilayer network, interdependent network reciprocity this work must maintain attribution to the author(s) and the title of the work, journal citation Abstract and DOI. Understanding large-scale cooperation among unrelated individuals is one of the greatest challenges of the 21st century. Since human cooperation evolves on social networks, the theoretical framework of multilayer networks is perfectly suited for studying this fascinating aspect of our biology. -
Simple Rules for a Complex World with Artificial Intelligence
Simple Rules for a Complex World with Artificial Intelligence Jes´usFern´andez-Villaverde1 April 28, 2020 1University of Pennsylvania A complex world with AI and ML • It is hard to open the internet or browse a bookstore without finding an article or a book discussing artificial intelligence (AI) and, in particular, machine learning (ML). • I will define some of these concepts more carefully later on. • Many concerns: effects of AI and ML on jobs, wealth and income inequality, ... • Some observers even claim that gone is the era of large armies and powerful navies. The nations with the best algorithms, as the Roman said in the Aeneid, \will rule mankind, and make the world obey." 1 2 AI, ML, and public policy, I • One thread that increasingly appears in these works, and which is bound to become a prominent concern, is how AI can address policy questions. • Some proposals are mild. • For example, thanks to ML: 1. We might be able to detect early strains in the financial markets and allow regulatory agencies to respond before damage occurs. 2. We might be able to fight electronic fraud and money laundering. 3. We might be able to improve public health. • I do not have any problem with these applications. Natural extension of models used in econometrics for decades. 3 AI, ML, and public policy, II • Some proposals are radical: \digital socialism" (Saros, 2014, Phillips and Rozworski, 2019, and Morozov, 2019). • The defenders of this view argue that some form of AI or ML can finally achieve the promise of central planning: we will feed a computer (or a system of computers) all the relevant information and, thanks to ML (the details are often fuzzy), we will get an optimal allocation of goods and income. -
Inheritance Patterns in Citation Networks Reveal Scientific Memes
Research Collection Journal Article Inheritance Patterns in Citation Networks Reveal Scientific Memes Author(s): Kuhn, Tobias; Perc, Matjaž; Helbing, Dirk Publication Date: 2014 Permanent Link: https://doi.org/10.3929/ethz-b-000091867 Originally published in: Physical Review X 4(4), http://doi.org/10.1103/PhysRevX.4.041036 Rights / License: Creative Commons Attribution 3.0 Unported This page was generated automatically upon download from the ETH Zurich Research Collection. For more information please consult the Terms of use. ETH Library PHYSICAL REVIEW X 4, 041036 (2014) Inheritance Patterns in Citation Networks Reveal Scientific Memes Tobias Kuhn,1,* Matjaž Perc,2,3 and Dirk Helbing1,4 1ETH Zurich, Clausiusstrasse 50, 8092 Zurich, Switzerland 2Faculty of Natural Sciences and Mathematics, University of Maribor, Koroška cesta 160, SI-2000 Maribor, Slovenia 3CAMTP—Center for Applied Mathematics and Theoretical Physics, University of Maribor, Krekova 2, SI-2000 Maribor, Slovenia 4Risk Center, ETH Zurich, Scheuchzerstrasse 7, 8092 Zurich, Switzerland (Received 8 July 2014; revised manuscript received 19 September 2014; published 21 November 2014) Memes are the cultural equivalent of genes that spread across human culture by means of imitation. What makes a meme and what distinguishes it from other forms of information, however, is still poorly understood. Our analysis of memes in the scientific literature reveals that they are governed by a surprisingly simple relationship between frequency of occurrence and the degree to which they propagate along the citation graph. We propose a simple formalization of this pattern and validate it with data from close to 50 million publication records from the Web of Science, PubMed Central, and the American Physical Society. -
Error Correction. Chilean Cybernetics and Chicago's Economists
[2] Error Correction: Chilean Cybernetics and Chicago’s Economists Adrian Lahoud Cybernetics is a specific way of conceiving the relation between information and government: It represented a way of bringing the epistemological and the onto- logical together in real time. The essay explores a par- adigmatic case study in the evolution of this history: the audacious experiment in cybernetic management known as Project Cybersyn that was developed follow- ing Salvador Allende’s ascension to power in Chile in 1970. In ideological terms, Allende’s socialism and the violent doctrine of the Chicago School could not be more opposed. In another sense, however, Chilean cybernetics would serve as the prototype for a new form of governance that would finally award to the theories of the Chicago School a hegemonic control over global society. In Alleys of Your Mind: Augmented Intellligence and Its Traumas, edited by Matteo Pasquinelli, 37–51. Lüneburg: meson press, 2015. DOI: 10.14619/014 38 Alleys of Your Mind Zero Latency Agreatdealoftimehasbeenspentinvestigating,documentinganddisputing anelevenyearperiodinChilefrom1970–1981,encompassingthepresidency ofSalvadorAllendeandthedictatorshipofAugustoPinochet.Betweenthe rise of the Unidad Popular anditsoverthrowbythemilitaryjunta,brutaland notorious events took hold of Chile.1 Though many of these events have remainedambiguous,obscuredbytraumaorlostinofficialdissimulation,over timethecontoursofhistoryhavebecomelessconfused.Beyondthecoup,the involvement of the United States or even the subsequent transformation of the economy, a more comprehensive story of radical experimentation on the Chileansocialbodyhasemerged.AtstakeintheyearsofAllende’sascension to power and those that followed was nothing less than a Latin social labora- tory.Thislaboratorywasatonceoptimistic,sincere,naïve,andfinallybrutal. FewexperimentswereasaudaciousorpropheticasAllende’scybernetic program Cybersyn.