Human Computer Interactions in Next-Generation of Aircraft Smart Navigation Management Systems: Task Analysis and Architecture under an Agent-Oriented Methodological Approach

The limited efficiency of current air traffic systems will require a next-generation of Smart Air Traffic System (SATS) that relies on current technological advances. This challenge means a transition toward a new navigation and air-traffic procedures paradigm, where pilots and air traffic controllers perform and coordinate their activities according to new roles and technological supports. The design of new Human-Computer Interactions (HCI) for performing these activities is a key element of SATS. However efforts for developing such tools need to be inspired on a parallel characterization of hypothetical air traffic scenarios compatible with current ones. This paper is focused on airborne HCI into SATS where cockpit inputs came from aircraft navigation systems, surrounding traffic situation, controllers' indications, etc. So the HCI is intended to enhance situation awareness and decision-making through pilot cockpit. This work approach considers SATS as a system distributed on a large-scale with uncertainty in a dynamic environment. Therefore, a multi-agent systems based approach is well suited for modeling such an environment. We demonstrate that current methodologies for designing multi-agent systems are a useful tool to characterize HCI. We specifically illustrate how the selected methodological approach provides enough guidelines to obtain a cockpit HCI design that complies with future SATS specifications.This work was supported in part by Projects MINECO TEC2011-28626-C02-01/02, by program CENIT-ATLANTIDA (cofinanced by Indra and Boeing R&TE), and by ULPGC Precompetitive Research Project (ULPGC Own Program).Publicad

Multi-Agent Systems

[EN] With the current advance of technology, agent-based applications are becoming a standard in a great variety of domains such as e-commerce, logistics, supply chain management, telecommunications, healthcare, and manufacturing. Another reason for the widespread interest in multi-agent systems is that these systems are seen as a technology and a tool that helps in the analysis and development of new models and theories in large-scale distributed systems or in human-centered systems. This last aspect is currently of great interest due to the need for democratization in the use of technology that allows people without technical preparation to interact with the devices in a simple and coherent way. In this Special Issue, different interesting approaches that advance this research discipline have been selected and presented.Julian Inglada, VJ.; Botti V. (2019). Multi-Agent Systems. Applied Sciences. 9(7):1-7. https://doi.org/10.3390/app9071402S1797Kravari, K., & Bassiliades, N. (2015). A Survey of Agent Platforms. Journal of Artificial Societies and Social Simulation, 18(1). doi:10.18564/jasss.2661Baldoni, M., Baroglio, C., May, K., Micalizio, R., & Tedeschi, S. (2018). Computational Accountability in MAS Organizations with ADOPT. Applied Sciences, 8(4), 489. doi:10.3390/app8040489Boissier, O., Bordini, R. H., Hübner, J. F., Ricci, A., & Santi, A. (2013). Multi-agent oriented programming with JaCaMo. Science of Computer Programming, 78(6), 747-761. doi:10.1016/j.scico.2011.10.004Challenger, M., Tezel, B., Alaca, O., Tekinerdogan, B., & Kardas, G. (2018). Development of Semantic Web-Enabled BDI Multi-Agent Systems Using SEA_ML: An Electronic Bartering Case Study. Applied Sciences, 8(5), 688. doi:10.3390/app8050688Challenger, M., Demirkol, S., Getir, S., Mernik, M., Kardas, G., & Kosar, T. (2014). On the use of a domain-specific modeling language in the development of multiagent systems. Engineering Applications of Artificial Intelligence, 28, 111-141. doi:10.1016/j.engappai.2013.11.012Boztepe, İ., & Erdur, R. (2018). Linked Data Aware Agent Development Framework for Mobile Devices. Applied Sciences, 8(10), 1831. doi:10.3390/app8101831Shoham, Y., Powers, R., & Grenager, T. (2007). If multi-agent learning is the answer, what is the question? Artificial Intelligence, 171(7), 365-377. doi:10.1016/j.artint.2006.02.006Duan, K., Fong, S., Zhuang, Y., & Song, W. (2018). Artificial Neural Networks in Coordinated Control of Multiple Hovercrafts with Unmodeled Terms. Applied Sciences, 8(6), 862. doi:10.3390/app8060862Zhang, Q., Yao, J., Yin, Q., & Zha, Y. (2018). Learning Behavior Trees for Autonomous Agents with Hybrid Constraints Evolution. Applied Sciences, 8(7), 1077. doi:10.3390/app8071077Cook, D. J., Augusto, J. C., & Jakkula, V. R. (2009). Ambient intelligence: Technologies, applications, and opportunities. Pervasive and Mobile Computing, 5(4), 277-298. doi:10.1016/j.pmcj.2009.04.001Kranz, M., Holleis, P., & Schmidt, A. (2010). Embedded Interaction: Interacting with the Internet of Things. IEEE Internet Computing, 14(2), 46-53. doi:10.1109/mic.2009.141Gershenfeld, N., Krikorian, R., & Cohen, D. (2004). The Internet of Things. Scientific American, 291(4), 76-81. doi:10.1038/scientificamerican1004-76Atzori, L., Iera, A., & Morabito, G. (2010). The Internet of Things: A survey. Computer Networks, 54(15), 2787-2805. doi:10.1016/j.comnet.2010.05.010Costa, A., Novais, P., Corchado, J. M., & Neves, J. (2011). Increased performance and better patient attendance in an hospital with the use of smart agendas. Logic Journal of IGPL, 20(4), 689-698. doi:10.1093/jigpal/jzr021Tapia, D. I., & Corchado, J. M. (2009). An Ambient Intelligence Based Multi-Agent System for Alzheimer Health Care. International Journal of Ambient Computing and Intelligence, 1(1), 15-26. doi:10.4018/jaci.2009010102Barriuso, A., De la Prieta, F., Villarrubia González, G., De La Iglesia, D., & Lozano, Á. (2018). MOVICLOUD: Agent-Based 3D Platform for the Labor Integration of Disabled People. Applied Sciences, 8(3), 337. doi:10.3390/app8030337Rosales, R., Castañón-Puga, M., Lara-Rosano, F., Flores-Parra, J., Evans, R., Osuna-Millan, N., & Gaxiola-Pacheco, C. (2018). Modelling the Interaction Levels in HCI Using an Intelligent Hybrid System with Interactive Agents: A Case Study of an Interactive Museum Exhibition Module in Mexico. Applied Sciences, 8(3), 446. doi:10.3390/app8030446Ramos, J., Oliveira, T., Satoh, K., Neves, J., & Novais, P. (2018). Cognitive Assistants—An Analysis and Future Trends Based on Speculative Default Reasoning. Applied Sciences, 8(5), 742. doi:10.3390/app8050742SATOH, K. (2005). Speculative Computation and Abduction for an Autonomous Agent. IEICE Transactions on Information and Systems, E88-D(9), 2031-2038. doi:10.1093/ietisy/e88-d.9.2031Miyashita, K. (2017). Incremental Design of Perishable Goods Markets through Multi-Agent Simulations. Applied Sciences, 7(12), 1300. doi:10.3390/app7121300Albino, V., Berardi, U., & Dangelico, R. M. (2015). Smart Cities: Definitions, Dimensions, Performance, and Initiatives. Journal of Urban Technology, 22(1), 3-21. doi:10.1080/10630732.2014.942092Roscia, M., Longo, M., & Lazaroiu, G. C. (2013). Smart City by multi-agent systems. 2013 International Conference on Renewable Energy Research and Applications (ICRERA). doi:10.1109/icrera.2013.6749783Lozano, Á., De Paz, J., Villarrubia González, G., Iglesia, D., & Bajo, J. (2018). Multi-Agent System for Demand Prediction and Trip Visualization in Bike Sharing Systems. Applied Sciences, 8(1), 67. doi:10.3390/app8010067Jordán, J., Palanca, J., del Val, E., Julian, V., & Botti, V. (2018). A Multi-Agent System for the Dynamic Emplacement of Electric Vehicle Charging Stations. Applied Sciences, 8(2), 313. doi:10.3390/app8020313Billhardt, H., Fernández, A., Lujak, M., & Ossowski, S. (2018). Agreement Technologies for Coordination in Smart Cities. Applied Sciences, 8(5), 816. doi:10.3390/app805081

Embedding smart software agents in resource constrained Internet of Things devices

[ES]Los sistemas de sensorización en combinación con herramientas de tratamiento y gestión inteligente de información, constituyen la base sobre la que se construirán las ciudades y entornos urbanos del futuro. Avanzar en la investigación y desarrollo de estos nuevos escenarios inteligentes, es fundamental a la hora de alcanzar los objetivos de eficiencia, integración, sostenibilidad y calidad de vida de las personas que habitan nuestras ciudades. Para alcanzar estos objetivos, es fundamental indagar en el desarrollo de dispositivos hardware más baratos, precisos e inteligentes que serán la base de los entornos inteligentes del futuro. Debido a las previsiones realizadas para los próximos años, la cantidad de dispositivos conectados a Internet será de hasta 7 dispositivos por cada persona en el planeta. Esta avalancha de dispositivos llevará asociada una avalancha de datos que tendrán que ser manejados y almacenados por los centros de procesamiento de datos. Por todo ello, avanzar en el diseño de herramientas para el procesamiento de datos inteligente, así como en nuevos dispositivos de sensorización, es una tarea de vital importancia para la viabilidad futura de los entornos conectados. Por ello, en este trabajo de tesis doctoral se propone un sistema inteligente basado en agentes embebidos en dispositivos inalámbricos con capacidades reducidas (memoria y capacidad de cómputo limitada), para entornos del Internet de las cosas (IoT) donde sea posible un procesamiento inteligente de datos. En particular, se presenta una novedosa arquitectura multi-agente enfocada a la gestión de los datos generados por los dispositivos IoT, sobre la que construir una capa de servicios adaptada a las diferentes necesidades de los distintos entornos donde será posible desplegar el sistema de sensorización. Con el objetivo de validad el sistema propuesto, se ha diseñado un caso de estudio basado en redes de sensores en un entorno IoT de eficiencia energética a través de la optimización del consumo de batería de una bicicleta eléctrica

Studying Software Engineering Patterns for Designing Machine Learning Systems

Machine-learning (ML) techniques have become popular in the recent years. ML techniques rely on mathematics and on software engineering. Researchers and practitioners studying best practices for designing ML application systems and software to address the software complexity and quality of ML techniques. Such design practices are often formalized as architecture patterns and design patterns by encapsulating reusable solutions to commonly occurring problems within given contexts. However, to the best of our knowledge, there has been no work collecting, classifying, and discussing these software-engineering (SE) design patterns for ML techniques systematically. Thus, we set out to collect good/bad SE design patterns for ML techniques to provide developers with a comprehensive and ordered classification of such patterns. We report here preliminary results of a systematic-literature review (SLR) of good/bad design patterns for ML

Synthesising process controllers from formal models of transformable assembly systems

When producing complex and highly customisable products in low volumes (or in ‘batch sizes of one’), automation of production systems is critical for competitiveness and profitability in high labour-cost economies. To facilitate batch-size-of-one production, ‘topology generation’, ‘realisability’, and ‘control’ algorithms have been developed as part of the Evolvable Assembly Systems (EAS) project. The topology generation algorithm computes all the possible sequences of parallel activities that assembly resources can perform on parts and is run offline whenever the layout of the production facility changes, whereas realisability checking and controller generation are performed at run-time to check whether a production facility with a given set of assembly resources can assemble a desired product, and how the product should be assembled, e.g., which resources to use, and when. Generated controllers are output in Business to Manufacturing Markup Language (B2MML). Taken together, the algorithms thus represent a step toward a complete path from the formal specification of an assembly system and the products to be assembled, to the automated synthesis of executable process plans. This paper presents each algorithm in sufficient detail to allow their reimplementation by other researchers. Topology generation is the most expensive step in the approach. A preliminary experimental evaluation of the scalability of topology generation is presented, which suggests that, for small to medium sized production facilities, the time required for recomputing the topology is sufficiently small not to preclude frequent factory transformations, e.g., the addition of new resources.Funded by the Engineering and Physical Sciences Research Council via grants EP/K018205/1 and EP/K014161/1

Hybrid Cloud Model Checking Using the Interaction Layer of HARMS for Ambient Intelligent Systems

Soon, humans will be co-living and taking advantage of the help of multi-agent systems in a broader way than the present. Such systems will involve machines or devices of any variety, including robots. These kind of solutions will adapt to the special needs of each individual. However, to the concern of this research effort, systems like the ones mentioned above might encounter situations that will not be seen before execution time. It is understood that there are two possible outcomes that could materialize; either keep working without corrective measures, which could lead to an entirely different end or completely stop working. Both results should be avoided, specially in cases where the end user will depend on a high level guidance provided by the system, such as in ambient intelligence applications. This dissertation worked towards two specific goals. First, to assure that the system will always work, independently of which of the agents performs the different tasks needed to accomplish a bigger objective. Second, to provide initial steps towards autonomous survivable systems which can change their future actions in order to achieve the original final goals. Therefore, the use of the third layer of the HARMS model was proposed to insure the indistinguishability of the actors accomplishing each task and sub-task without regard of the intrinsic complexity of the activity. Additionally, a framework was proposed using model checking methodology during run-time for providing possible solutions to issues encountered in execution time, as a part of the survivability feature of the systems final goals

Агентна архітектура механізмів консенсусу в блокчейні

Магістерська дисертація: 100 с., 25 табл., 16 рис., 15 джерел, 1 додаток. Об’єкт дослідження — транзакції блокчейну в залежності від механізму консенсусу. Предмет дослідження — застосування методів штучного інтелекту та інтелектуальних агентів для підбору параметрів мережі блокчейн. Мета роботи — розробка агентної архітектури для аналізу блокчейну Ethereum, роботи його транзакційного механізму в умовах обраного механізму консенсусу та порівняння цих механізмів у вигляді зібраних метрик часу проходження транзакції, кількості витрачених ресурсів та безпечності концепту. В роботі проведено огляд різних механізмів консенсусу блокчейну в залежності від підібраних параметрів мережі за допомогою інтелектуальних агентів. Розглянуті сучасні методи штучного інтелекту в агентних архітектурах та їх роль у дослідженні світу криптовалют, і, в свою чергу, впливу криптовалют на довколишнє середовище. Зібрано дані ефективності використання наборів протоколів, стимулів та ідей, які дозволяють мережі вузлів погоджувати стан блокчейну в залежності від налаштування мережі, що дозволяє оцінити доцільність використання того чи іншого механізму консенсусу. Застосовано штучний інтелект для проведення збору та аналізу метрик часу проведення транзакцій, їх стійкості до зламу, кількості використаних обчислювальних ресурсів і відповідно кількості витраченої електроенергії.Master’s thesis: 100 p., 25 tab., 16 fig., 15 references, 1 appendix. The object of the research is blockchain transactions depending on the consensus mechanism. The subject of the research is the application of artificial intelligence methods and intelligent agents to select the parameters of the blockchain network. The purpose of the work is to develop an agent architecture for the analysis of the Ethereum blockchain, the operation of its transaction mechanism under the conditions of the selected consensus mechanism, and the comparison of these mechanisms in the form of collected metrics of transaction time, the amount of resources spent, and the safety of the concept. The paper provides an overview of various blockchain consensus mechanisms depending on selected network parameters with the help of intelligent agents. Modern methods of artificial intelligence in agent architectures and their role in researching the world of cryptocurrencies, and the impact of cryptocurrencies on the environment, are considered. Data on the effectiveness of using sets of protocols, incentives and ideas that allow a network of nodes to agree on the state of the blockchain depending on the configuration of the network have been collected, which makes it possible to assess the feasibility of using one or another consensus mechanism. Artificial intelligence was used to collect and analyze the metrics of transaction time, their resistance to hacking, the amount of computing resources used and, accordingly, the amount of electricity consumed

Estudo comparativo do uso de personas para o desenvolvimento de sistemas baseados em agentes

Trabalho de Conclusão de Curso (graduação)—Universidade de Brasília, Instituto de Ciências Exatas, Departamento de Ciência da Computação, 2017.O avanço das tecnologias de informação e comunicação têm transformado a forma como as pessoas se relacionam com os Sistemas de Informação (SI). Os diferentes perfis dos usuários e o ambiente no qual eles estão inseridos exercem grande influência sobre como um SI deve atender suas necessidades. Umas das formas de representar esse cenário é por meio de Sistemas Multiagentes (SMA), onde o ambiente é trabalhado em termos dos diferentes atores, responsabilidades, objetivos, tarefas e recursos. Imagina-se que personas servem como uma especificação dos usuários do sistema sendo mais especificas que os perfis de usuários. Assim, elas também devem exercer uma grande influência sobre como o SI deve funcionar. Com intuito de verificar a utilidade de personas no desenvolvimento de SMAs apresenta-se um estudo comparativo no cenário de vida assistida entre dois processos de desenvolvimento. Um que se baseia em personas e o outro não. Por meio da comparação dos processos foram encontrados indícios de que as personas provém uma visão mais direcionada sobre as necessidades dos usuáriosThe advances of information and communication technologies has transformed the way people relates to Information Systems (IS). The different users’ profiles and the environment in which they are inserted exert great influence on how an IS must meet their needs. One of the ways of representing this scenario is by Multiagent Systems (MAS), where the environment is understood in terms of different actors, responsibilities, objectives, tasks and resources. It is imagined that personas serve epecification of users of the system being even more specific than user profiles. Thus, they must also exert a great influence on how the IS should work. In order to discover how personas can help in the development of MASs we present a comparative study in the assisted living scenario between two development processes. One based on personas and one that isn’t. Through the comparison of the processes evidences that personas direct the development to the users necessitys were found

A framework for active software engineering ontology

The passive structure of ontologies results in the ineffectiveness to access and manage the knowledge captured in them. This research has developed a framework for active Software Engineering Ontology based on a multi-agent system. It assists software development teams to effectively access, manage and share software engineering knowledge as well as project information to enable effective and efficient communication and coordination among teams. The framework has been evaluated through the prototype system as proof-of-concept experiments