Suchergebnisse

Proceedings of: 23rd International Conference on Industrial Engineering and Other Applications of Applied intelligent Systems, IEA/AIE 2010, Cordoba, Spain, June 1-4, 2010 ; Our proposal is to apply a Game Theoretic approach to the games played in Agent Reputation and Trust Final Competitions. Using such testbed, three international competitions were successfully carried out jointly with the last AAMAS international Conferences. The corresponding way to define the winner of such competitions was to run a game with all the participants (16). Our point is that such game does not represent a complete way to determine the best trust/reputation strategy, since it is not proved that such strategy is evolutionarily stable. Specifically we prove that when the strategy of the winner of the two first international competitions (2006 and 2007) becomes dominant, it is defeated by other participant trust strategies. Then we found out (through a repeated game definition) the right equilibrium of trust strategies that is evolutionarily stable. This kind of repeated game has to be taken into account in the evaluation of trust strategies, and this conclusion would improve the way trust strategies have to be compared. ; This work was supported in part by Projects CICYT TIN2008-06742-C02-02/ TSI, CICYT TEC2008-06732-C02-02/TEC, SINPROB, CAM MADRINET S-0505/TIC/0255 and DPS2008-07029-C02-02. ; Publicado

Intro -- Preface -- About This Book -- Contents -- About the Editors -- 1 An Introduction and Systematic Review on Machine Learning for Smart Environments/Cities: An IoT Approach -- 1.1 Introduction -- 1.2 Smart Environments, Internet of Things, and Machine Learning Concepts -- 1.2.1 Smart Environments -- 1.2.2 Internet of Things -- 1.2.3 Machine Learning -- 1.3 Results -- 1.3.1 Smart Cities -- 1.3.2 Smart Homes -- 1.3.3 Smart Buildings -- 1.3.4 Smart Health -- 1.3.5 Smart Grids -- 1.3.6 Smart Transportation -- 1.3.7 Smart Industries -- 1.4 Discussion -- 1.5 Conclusions -- References -- Part I Smart Environments -- 2 Model-Based Digital Threads for Socio-Technical Systems -- 2.1 Introduction -- 2.2 Digital Thread -- 2.2.1 Definition -- 2.2.2 Digital Representations -- 2.2.3 Digital Twins -- 2.2.4 Digital Twin Dimensions -- 2.3 Development Methodology -- 2.3.1 Model-Driven System Engineering (MBSE) -- 2.3.2 Models and Data -- 2.3.3 Life Cycle Support -- 2.4 Traffic Monitoring System (TMS) -- 2.5 The TMS Digital Twin Modeling Case -- 2.5.1 Concept Exploration -- 2.5.2 Preliminary Design -- 2.5.3 Remaining Development Phases -- 2.6 SysML v2 Improvements -- 2.7 Conclusion -- References -- 3 IoT Regulated Water Quality Prediction Through Machine Learning for Smart Environments -- 3.1 Introduction -- 3.2 Literature Review -- 3.3 Dataset Description -- 3.4 Methodology -- 3.5 Results and Discussion -- 3.6 Conclusion -- References -- 4 The Power of Augmented Reality for Smart Environments: An Explorative Analysis of the Business Process Management -- 4.1 Introduction -- 4.1.1 Research Design -- 4.2 The Historical Evolution of Augmented Reality for Smart Environments -- 4.3 Augmented Reality and Business Process Management -- 4.3.1 Smart Environment -- 4.4 Case Studies from Different Sectors -- 4.4.1 Methodology -- 4.4.2 Cases Study Description.

New applications are continuously appearing with drones as protagonists, but all of them share an essential critical maneuver—landing. New application requirements have led the study of novel landing strategies, in which vision systems have played and continue to play a key role. Generally, the new applications use the control and navigation systems embedded in the aircraft. However, the internal dynamics of these systems, initially focused on other tasks such as the smoothing trajectories between different waypoints, can trigger undesired behaviors. In this paper, we propose a landing system based on monocular vision and navigation information to estimate the helipad global position. In addition, the global estimation system includes a position error correction module by cylinder space transformation and a filtering system with a sliding window. To conclude, the landing system is evaluated with three quality metrics, showing how the proposed correction system together with stationary filtering improves the raw landing system. ; This research was partially funded by public research projects of Spanish Ministry of Science and Innovation, references PID2020-118249RB-C22 and PDC2021-121567-C22—AEI/10.13039/ 501100011033, and by the Madrid Government (Comunidad de Madrid, Spain) under the Multiannual Agreement with UC3M in the line of Excellence of University Professors, reference EPUC3M17.

This article belongs to the Special Issue Information Fusion and Machine Learning for Sensors. ; Certain difficulties in path forecasting and filtering problems are based in the initial hypothesis of estimation and filtering techniques. Common hypotheses include that the system can be modeled as linear, Markovian, Gaussian, or all at one time. Although, in many cases, there are strategies to tackle problems with approaches that show very good results, the associated engineering process can become highly complex, requiring a great deal of time or even becoming unapproachable. To have tools to tackle complex problems without starting from a previous hypothesis but to continue to solve classic challenges and sharpen the implementation of estimation and filtering systems is of high scientific interest. This paper addresses the forecast–filter problem from deep learning paradigms with a neural network architecture inspired by natural language processing techniques and data structure. Unlike Kalman, this proposal performs the process of prediction and filtering in the same phase, while Kalman requires two phases. We propose three different study cases of incremental conceptual difficulty. The experimentation is divided into five parts: the standardization effect in raw data, proposal validation, filtering, loss of measurements (forecasting), and, finally, robustness. The results are compared with a Kalman filter, showing that the proposal is comparable in terms of the error within the linear case, with improved performance when facing non-linear systems. ; This research was funded by public research projects of Spanish Ministry of Economy and Competitivity (MINECO), reference TEC2017-88048-C2-2-R and by the Madrid Government under the Multiannual Agreement with UC3M in the line of Excellence of University Professors (EPUC3M17), and in the context of the V PRICIT (Regional Programme of Research and Technological Innovation).

Proceedings of: 15th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL 2014), Salmanca, Spain, ; In this paper we present a proposal to develop conversational agents that avoids the effort of manually defining the dialog strategy for the agent and also takes into account the benefits of using current standards. In our proposal the dialog manager is trained by means of a POMDP-based methodology using a labeled dialog corpus automatically acquired using a user modeling technique. The statistical dialog model automatically selects the next system response. Thus, system developers only need to define a set of files, each including a system prompt and the associated grammar to recognize user responses. We have applied this technique to develop a conversational agent in VoiceXML that provides information for planning a trip. ; This work has been supported in part by the Spanish Government under i-Support (Intelligent Agent Based Driver Decision Support) Project (TRA2011-29454-C03- 03), and Projects MINECO TEC2012-37832-C02-01, CICYT TEC2011-28626-C02- 02, and CAM CONTEXTS (S2009/TIC-1485)

According To The World Health Organization, Between 2000 And 2050, The Propor Tion Of The World' S Population Over 60 Will Double, From 11% To 22%. In Absolute Numbers, This Age Group Will Increase From 605 Million To 2 Billion In The Course Of Half A Century. It Is A Reality That Most Of Them Prefer To Live Alone, So It Is Necessary To Look For Mechanisms And Tools That Will Help Them To Improve Their Autonomy. Although In Recent Years, We Have Been Living In A Veritable Explosion Of Domotic Sys Tems That Facilitate People' S Daily Lives, It Is Also True That There Are Not Many Tools Specifically Aimed At This Sector Of The Population. The Aim Of This Paper Is To Present A Potential Solution To The Monitoring Of Activity Of Daily Living In The Least Intrusive Way For People. In This Case, Anomalous Patterns Of Daily Activities Will Be Detected By Analysing The Daily Consumption Of Household Appliances. People Who Live Alone Usu Ally Have A Pattern Of Daily Behaviour In The Use Of Household Appliances (Coffee Machine, Microwave, Television, Etc.). A Neuronal Model Is Proposed For The Detection Of Abnormal Behaviour Based On An Autoencoder Architecture. This Solution Will Be Compared With A Variational Autoencoder To Analyse The Improvements That Can Be Obtained. The Well-Known Dataset Called Uk-Dale Will Be Used To Validate The Proposal. ; V PRICIT (Regional Programme of Research and Technological Innovation); Madrid Government (Comunidad de Madrid-Spain); Universidad Carlos III de Madrid, and Competitiveness (MINECO), Grant/Award Numbers: RTC-2016-5059-8, RTC-2016-5191-8, RTC-2016-5595-2, TEC2017-88048-C2-2-R; Spanish Ministry of Economy; Company MasMovil

AbstractLocal governments dispose of powerful tools like development funds that can be distributed among its different constituents to compensate economic disequilibrium originated by a complex array of factors. But it is always one of the hardest decisions to assign handouts to people who could think its own expectations are not being taken properly into account. Each stakeholder has different criteria to evaluate his needs, and to demand a particular investment effort. Since resources are very limited in local levels, city hall governments are pulled apart by those conflicting demands. The challenge of addressing them at the same time can be modelled as a multi‐criteria decision‐making. The aim of this paper is to show that the analytic hierarchy process (AHP) could work out the most acceptable distribution of the funds among the different city districts and neighbourhoods. The application of the model in Madrid shows that AHP: (a) allows to incorporate opposing demands; (b) increases the transparency of the decision‐making process; (c) eases the decentralization of governmental decisions; (d) enhances the legitimation of the final outcome; and (e) it is a scientific approach with great potential to be applied in similar domains where hard political decisions are needed.

Microgrids should be continuously monitored in order to maintain suitable voltages over time. Microgrids are mainly monitored remotely, and their measurement data transmitted through lossy communication networks are vulnerable to cyberattacks and packet loss. The current study leverages the idea of data fusion to address this problem. Hence, this paper investigates the effects of estimation fusion using various machine-learning (ML) regression methods as data fusion methods by aggregating the distributed Kalman filter (KF)-based state estimates of a linear smart microgrid in order to achieve more accurate and reliable state estimates. This unreliability in measurements is because they are received through a lossy communication network that incorporates packet loss and cyberattacks. In addition to ML regression methods, multi-layer perceptron (MLP) and dependent ordered weighted averaging (DOWA) operators are also employed for further comparisons. The results of simulation on the IEEE 4-bus model validate the effectiveness of the employed ML regression methods through the RMSE, MAE and R-squared indices under the condition of missing and manipulated measurements. In general, the results obtained by the Random Forest regression method were more accurate than those of other methods. ; This research was partially funded by public research projects of Spanish Ministry of Science and Innovation, references PID2020-118249RB-C22 and PDC2021-121567-C22 - AEI/10.13039/ 501100011033, and by the Madrid Government (Comunidad de Madrid-Spain) under the Multiannual Agreement with UC3M in the line of Excellence of University Professors, reference EPUC3M17.

21 pages, 21 figures.-- Journal special issue on Visual Sensor Networks. ; The recent interest in the surveillance of public, military, and commercial scenarios is increasing the need to develop and deploy intelligent and/or automated distributed visual surveillance systems. Many applications based on distributed resources use the so-called software agent technology. In this paper, a multi-agent framework is applied to coordinate videocamera-based surveillance. The ability to coordinate agents improves the global image and task distribution efficiency. In our proposal, a software agent is embedded in each camera and controls the capture parameters. Then coordination is based on the exchange of high-level messages among agents. Agents use an internal symbolic model to interpret the current situation from the messages from all other agents to improve global coordination. ; This work was funded by projects CICYT TSI2005-07344, CICYT TEC2005-07186, and CAM MADRINET S-0505/TIC/0255. ; Publicado