La memoria

La memoria es uno de los componentes principales del ordenador y uno de los conceptos en los que se basa cualquier ordenador, desde las primeras máquina de los años 40 hasta nuestros días. La idea de programa almacenado en la memoria es una característica común a todos ellos. La memoria principal de un ordenador es la memoria RAM, en la que se almacenan temporalmente las instrucciones y los datos de todos los programas que están actualmente en ejecución. Además de la memoria RAM, existen otros tipos de memoria. Las más habituales son las memorias ROM, CMOS.Rebollo Pedruelo, M. (2011). La memoria. http://hdl.handle.net/10251/1078

Dispositivos de salida

Los ordenadores necesitan dispositivos de salida para mostrar los resultados de las operaciones que realiza el ordenador. Los dispositivos de salida más usuales son dos: el monitor y la impresora. El monitor es un dispositivo que emite luz y con ella activa los puntos que forman la imagen en la pantalla. Dependiendo de la tecnología con la que están construidos, distinguiremos entre CRT y LCD. La calidad de la imagen depende de la resolución del monitor (el número de píxeles que puede mostrar). Encontramos pantallas que van desde las 5", como en el caso de los libros electrónicos, hasta las 30" que puede tener el monitor de un ordenador de sobremesa. Si necesitamos conservar una salida, las impresoras permiten obtener una copia impresa de lo que vemos en pantalla. Las impresoras más comunes son las de inyección de tinta, aunque existen otros tipos de impresoras como las láser o las impresoras fotográficas que permiten obtener resultados profesionales de mayor calidad o con mayor rapidez. La forma de conseguir las imágenes en ambos medios es distinta. En el caso de los monitores, se emplea un esquema RGB, ya que la luz se descompone en estos tres colores: rojo verde y azul (RGB por sus iniciales en inglés). En el caso de la luz reflejada, que es lo que vemos en el papel, los colores primarios son el cían, el amarillo y el magenta. Si añadimos el negro, tenemos los esquelas CMYK (también por los nombres de los colores correspondientes en inglés).Rebollo Pedruelo, M. (2011). Dispositivos de salida. http://hdl.handle.net/10251/1368

Dispositivos de almacenamiento

Los ordenadores necesitan dispositivos de almacenamiento para guardar de forma definitiva los datos con los que trabajan, ya que la información de la memoria principal se pierde cuando se interrumpe la corriente eléctrica. Hoy en día podemos encontrar 3 tipos de dispositivos, basados en tecnologías distintas para almacenar la información: (i) dispositivos magnéticos, como cintas, disquetes (ya en desuso) y discos duros, que son los más empleados; (ii) dispositivos ópticos, como CD-ROM, DVD y discos Blu-ray; (iii) memoria de estado sólido, comúnmente conocida como memoria flash, empleada en memorias USB, tarjetas y recientemente en discos SSD. A pesar de llamarse 'memoria', no debe confundirse con la RAM del ordenador: es un dispositivo de entrada/salida.Rebollo Pedruelo, M. (2011). Dispositivos de almacenamiento. http://hdl.handle.net/10251/1370

Dispositivos de entrada

Los dispositivos de entrada se emplean introducir la información que debe ser procesada en el ordenador. Los dispositivos más usuales son el teclado y el ratón. En ordenadores portátiles hay otros tipos de dispositivos señalizadores, como paneles táctiles con la misma función. Otros dispositivos están especializados en leer entradas en un formato determinados, como los códigos de barras, de puntos o los códigos QR actuales. Dado que la naturaleza de la información que podemos manipular es muy diversa, existen multitud de dispositivos de entrada adaptados a los distintos tipo de señales. En este caso es necesario convertir la información que proviene del mundo exterior, habitualmente en formato analógico, en formato digital, que puede ser almacenado y procesado en el ordenador. Los dispositivos que realizan esta función reciben en general el nombre de dispositivos digitalizadores. Principalmente nos encontraremos digitalizadores de imágenes, de audio y de vídeo (una combinación de los dos anteriores). En todos los casos el proceso es similar: se toman muestras discretas de la señal original y se convierten en valores binarios. Dependiendo del número de muestras que se tomen y del número de bits con los que se codifiquen los valores que se obtienen tendremos un archivo de mayor o menor calidad.Rebollo Pedruelo, M. (2011). Dispositivos de entrada. http://hdl.handle.net/10251/1368

Supportive consensus

[EN] The paper is concerned with the consensus problem in a multi-agent system such that each agent has boundary constraints. Classical Olfati-Saber's consensus algorithm converges to the same value of the consensus variable, and all the agents reach the same value. These algorithms find an equality solution. However, what happens when this equality solution is out of the range of some of the agents? In this case, this solution is not adequate for the proposed problem. In this paper, we propose a new kind of algorithms called supportive consensus where some agents of the network can compensate for the lack of capacity of other agents to reach the average value, and so obtain an acceptable solution for the proposed problem. Supportive consensus finds an equity solution. In the rest of the paper, we define the supportive consensus, analyze and demonstrate the network's capacity to compensate out of boundaries agents, propose different supportive consensus algorithms, and finally, provide some simulations to show the performance of the proposed algorithms.The author(s) received specific funding for this work from the Valencian Research Institute for Artificial Intelligence (VRAIN) where the authors are currently working. This work is partially supported by the Spanish Government project RTI2018-095390-B-C31, GVA-CEICE project PROMETEO/2018/002, and TAILOR, a project funded by EU Horizon 2020 research and innovation programme under GA No 952215. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Palomares Chust, A.; Rebollo Pedruelo, M.; Carrascosa Casamayor, C. (2020). Supportive consensus. 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A MAS-based infrastructure for negotiation and its application to a water-right market. Information Systems Frontiers, 16(2), 183-199. doi:10.1007/s10796-013-9443-8Rebollo M, Carrascosa C, Palomares A. Consensus in Smart Grids for Decentralized Energy Management. In: Highlights of Practical Applications of Heterogeneous Multi-Agent Systems. The PAAMS Collection. Springer; 2014. p. 250–261.Zhao, T., & Ding, Z. (2018). Distributed Agent Consensus-Based Optimal Resource Management for Microgrids. IEEE Transactions on Sustainable Energy, 9(1), 443-452. doi:10.1109/tste.2017.2740833Qiu, Z., Liu, S., & Xie, L. (2018). Necessary and sufficient conditions for distributed constrained optimal consensus under bounded input. International Journal of Robust and Nonlinear Control, 28(6), 2619-2635. doi:10.1002/rnc.4040Wei Ren, & Beard, R. W. (2005). Consensus seeking in multiagent systems under dynamically changing interaction topologies. IEEE Transactions on Automatic Control, 50(5), 655-661. doi:10.1109/tac.2005.846556Ren, W., & Beard, R. W. (2008). Distributed Consensus in Multi-vehicle Cooperative Control. Communications and Control Engineering. doi:10.1007/978-1-84800-015-5Knorn F, Corless MJ, Shorten RN. A result on implicit consensus with application to emissions control. In: 2011 50th IEEE Conference on Decision and Control and European Control Conference; 2011. p. 1299–1304.Roy, S. (2015). Scaled consensus. Automatica, 51, 259-262. doi:10.1016/j.automatica.2014.10.073Mo, L., & Lin, P. (2018). Distributed consensus of second-order multiagent systems with nonconvex input constraints. International Journal of Robust and Nonlinear Control, 28(11), 3657-3664. doi:10.1002/rnc.4076Wang, Q., Gao, H., Alsaadi, F., & Hayat, T. (2014). An overview of consensus problems in constrained multi-agent coordination. Systems Science & Control Engineering, 2(1), 275-284. doi:10.1080/21642583.2014.897658Xi, J., Yang, J., Liu, H., & Zheng, T. (2018). Adaptive guaranteed-performance consensus design for high-order multiagent systems. Information Sciences, 467, 1-14. doi:10.1016/j.ins.2018.07.069Fontan A, Shi G, Hu X, Altafini C. Interval consensus: A novel class of constrained consensus problems for multiagent networks. In: 2017 IEEE 56th Annual Conference on Decision and Control (CDC); 2017. p. 4155–4160.Hou, W., Wu, Z., Fu, M., & Zhang, H. (2018). Constrained consensus of discrete-time multi-agent systems with time delay. International Journal of Systems Science, 49(5), 947-953. doi:10.1080/00207721.2018.1433899Elhage N, Beal J. Laplacian-based consensus on spatial computers. In: AAMAS; 2010. p. 907–914.Cavalcante R, Rogers A, Jennings N. Consensus acceleration in multiagent systems with the Chebyshev semi-iterative method. In: Proc. of AAMAS’11; 2011. p. 165–172.Hu, H., Yu, L., Zhang, W.-A., & Song, H. (2013). Group consensus in multi-agent systems with hybrid protocol. Journal of the Franklin Institute, 350(3), 575-597. doi:10.1016/j.jfranklin.2012.12.020Ji, Z., Lin, H., & Yu, H. (2012). Leaders in multi-agent controllability under consensus algorithm and tree topology. Systems & Control Letters, 61(9), 918-925. doi:10.1016/j.sysconle.2012.06.003Li, Y., & Tan, C. (2019). A survey of the consensus for multi-agent systems. Systems Science & Control Engineering, 7(1), 468-482. doi:10.1080/21642583.2019.1695689Salazar, N., Rodriguez-Aguilar, J. A., & Arcos, J. L. (2010). Robust coordination in large convention spaces. AI Communications, 23(4), 357-372. doi:10.3233/aic-2010-0479Pedroche F, Rebollo M, Carrascosa C, Palomares A. On the convergence of weighted-average consensus. CoRR. 2013;abs/1307.7562

Strategies for cooperation emergence in distributed service discovery

This is an Accepted Manuscript of an article published by Taylor & Francis in Cybernetics and Systems on APR 3 2014], available online:http://www.tandfonline.com/10.1080/01969722.2014.894848[EN] In distributed environments where entities only have a partial view of the system, cooperation plays a key issue. In the case of decentralized service discovery in open agent societies, agents only know about the services they provide and who are their direct neighbors. Therefore, they need the cooperation of their neighbors in order to locate the required services. However, cooperation is not always present in open systems. Non-cooperative agents pursuing their own goals could refuse to forward queries from other agents to avoid the cost of this action; therefore, the efficiency of the decentralized service discovery could be seriously damaged. In this paper, we propose the ombination of incentives and local structural changes in order to promote cooperation in the service discovery process. The results show that, even in scenarios where the predominant behavior is not collaborative cooperation emerges.The work was partially supported by the Spanish Ministry of Science and Innovation through grants TIN2009-13839-C03-01, TIN2012-36586-C03-01, CSD2007-0022 (CONSOLIDER-INGENIO 2010).Del Val Noguera, E.; Rebollo Pedruelo, M.; Botti, V. (2014). Strategies for cooperation emergence in distributed service discovery. Cybernetics and Systems. 45(3):220-240. https://doi.org/10.1080/01969722.2014.894848S220240453Blanc , A. , Y.K. Liu , and A. Vahdat . “Designing Incentives for Peer-to-Peer Routing.” InProceedings of the 24th Annual Joint Conference of the IEEE Computer and Communications Societies, Vol. 1, pp. 374–385, 2005 .del Val , E. “Semantic Service Management in Service-Oriented Multi-Agent Systems.” Ph.D. thesis, Departament de Sistemes Informàtics i Computació, Universitat Politècnica de València, 2013 .Del Val, E., Rebollo, M., & Botti, V. (2012). 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An Empirical Investigation.” Paper presented at the 1st Workshop on Economics of Peer-to-Peer Systems, June 4–5, 2004, Harvard University .Hauert, C., Traulsen, A., Brandt, H., Nowak, M. A., & Sigmund, K. (2007). Via Freedom to Coercion: The Emergence of Costly Punishment. Science, 316(5833), 1905-1907. doi:10.1126/science.1141588Hofmann , L.M. , N. Chakraborty , and K. Sycara . “The Evolution of Cooperation in Self-Interested Agent Societies: A Critical Study.” InProceedings of the 10th International Conference on Autonomous Agents and Multiagent Systems, Volume 2 , edited by K. Tumer , P. Yolum , L. Sonenberg , and P. Stone , 685–692. IFAAMAS, 2011 .Lin, W. S., Zhao, H. V., & Liu, K. J. R. (2009). Incentive Cooperation Strategies for Peer-to-Peer Live Multimedia Streaming Social Networks. IEEE Transactions on Multimedia, 11(3), 396-412. doi:10.1109/tmm.2009.2012915Nowak, M. A. (2006). Five Rules for the Evolution of Cooperation. 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Improvement of Contact Tracing with Citizen's Distributed Risk Maps

[EN] The rapid spread of COVID-19 has demonstrated the need for accurate information to contain its diffusion. Technological solutions are a complement that can help citizens to be informed about the risk in their environment. Although measures such as contact traceability have been successful in some countries, their use raises society's resistance. This paper proposes a variation of the consensus processes in directed networks to create a risk map of a determined area. The process shares information with trusted contacts: people we would notify in the case of being infected. When the process converges, each participant would have obtained the risk map for the selected zone. The results are compared with the pilot project's impact testing of the Spanish contact tracing app (RadarCOVID). The paper also depicts the results combining both strategies: contact tracing to detect potential infections and risk maps to avoid movements into conflictive areas. Although some works affirm that contact tracing apps need 60% of users to control the propagation, our results indicate that a 40% could be enough. On the other hand, the elaboration of risk maps could work with only 20% of active installations, but the effect is to delay the propagation instead of reducing the contagion. With both active strategies, this methodology is able to significantly reduce infected people with fewer participants.This research was supported by TAILOR, a project funded by EU Horizon 2020 research and innovation programme under GA No 952215, and by the Spanish Ministry of Science, Innovation and Universities (MICIU) under Contract No. PGC2018-093854-B-I00b and RTI2018-095390-B-C32.Rebollo Pedruelo, M.; Benito, RM.; Losada, JC.; Galeano, J. (2021). Improvement of Contact Tracing with Citizen's Distributed Risk Maps. Entropy. 23(5):1-21. https://doi.org/10.3390/e23050638S12123

Analyzing urban mobility paths based on users' activity in social networks

[EN] This work presents an approach to model how the activity in social media of the citizens reflects the activity in the city. The proposal includes a gravitational model that deforms the surface of the city based on the intensity of the activity in different zones. The information is extracted from geolocated tweets (n = 1.48 x 10(6)). Furthermore, this activity affects how people move in a city. The path a user follows is calculated using the geolocation of the tweets that he or she publishes along the day. Several models are evaluated and compared using the Hausdorfs distance (d(H)). The combination of gravitational potential with attraction to the destination points provides the best results, with d(H) = 1176 against the Manhattan (d(H) = 1203) or the geodesic (d(H) = 1417) alternatives. Finally, the analysis is repeated with the data segmented by gender (n=2,826 paths, men=1,910, women=916). The results validate (p=0.000334) the studies that affirm that men travel longer distances (d(M) = 4.73 km, alpha(m) = 26.1 degrees) with rectilinear trajectories, whereas women have shorter and more angled paths (d(w) = 4.5 km, alpha(w) = 32.2 degrees), obtaining p values in path lengths and p=0.006 in the angles. (C) 2019 Elsevier B.V. All rights reserved.This work is partially supported by Spanish Government Project TIN2015-65515-C4-1-R and the Post-doc grant Ref. SP20170057.Rodríguez, L.; Palanca Cámara, J.; Del Val Noguera, E.; Rebollo Pedruelo, M. (2020). Analyzing urban mobility paths based on users' activity in social networks. Future Generation Computer Systems. 102:333-346. https://doi.org/10.1016/j.future.2019.07.072S33334610

Does the type of event influence how user interactions evolve on Twitter?

This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are creditedThe number of people using on-line social networks as a new way of communication is continually increasing. The messages that a user writes in these networks and his/her interactions with other users leave a digital trace that is recorded. Thanks to this fact and the use of network theory, the analysis of messages, user interactions, and the complex structures that emerge is greatly facilitated. In addition, information generated in on-line social networks is labeled temporarily, which makes it possible to go a step further analyzing the dynamics of the interaction patterns. In this article, we present an analysis of the evolution of user interactions that take place in television, socio-political, conference, and keynote events on Twitter. Interactions have been modeled as networks that are annotated with the time markers. We study changes in the structural properties at both the network level and the node level. As a result of this analysis, we have detected patterns of network evolution and common structural features as well as differences among the events.The author(s) received specific funding for this work from the research group (Grupo de Inteligencia Informatica e Inteligencia Artificial) where the authors are currently working. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Del Val Noguera, E.; Rebollo Pedruelo, M.; Botti Navarro, VJ. (2015). Does the type of event influence how user interactions evolve on Twitter?. PLoS ONE. 10(5):21-53. https://doi.org/10.1371/journal.pone.0124049S2153105Licoppe, C., & Smoreda, Z. (2005). Are social networks technologically embedded? 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Convergence of Weighted-average consensus for undirected graphs

[EN] In this note we address the problem of reaching a consensus in an undirected network where the nodes interchange information with their neighbors. Each node is provided with a value X_i and a weight w_i. The specific goal of the consensus is that each node will be aware of the weighted-average consensus value, in a distributed way, that is to say without a central control. We show the applicability of a theoretical result about reaching a consensus following an iterative algorithm.This work is supported by Spanish DGI grant MTM2010-18674, Consolider Ingenio CSD2007-00022, PROMETEO 2008/051, OVAMAH TIN2009-13839-C03-01, and PAID-06-11-2084.Pedroche Sánchez, F.; Rebollo Pedruelo, M.; Carrascosa Casamayor, C.; Palomares Chust, A. (2014). Convergence of Weighted-average consensus for undirected graphs. International Journal of Complex Systems in Science. 4(1):13-16. http://hdl.handle.net/10251/46244S13164