Towards formal models and languages for verifiable Multi-Robot Systems

Incorrect operations of a Multi-Robot System (MRS) may not only lead to unsatisfactory results, but can also cause economic losses and threats to safety. These threats may not always be apparent, since they may arise as unforeseen consequences of the interactions between elements of the system. This call for tools and techniques that can help in providing guarantees about MRSs behaviour. We think that, whenever possible, these guarantees should be backed up by formal proofs to complement traditional approaches based on testing and simulation. We believe that tailored linguistic support to specify MRSs is a major step towards this goal. In particular, reducing the gap between typical features of an MRS and the level of abstraction of the linguistic primitives would simplify both the specification of these systems and the verification of their properties. In this work, we review different agent-oriented languages and their features; we then consider a selection of case studies of interest and implement them useing the surveyed languages. We also evaluate and compare effectiveness of the proposed solution, considering, in particular, easiness of expressing non-trivial behaviour.Comment: Changed formattin

Nature-Inspired Coordination Models: Current Status and Future Trends

Coordination models and languages are meant to provide abstractions and mechanisms to harness the space of interaction as one of the foremost sources of complexity in computational systems. Nature-inspired computing aims at understanding the mechanisms and patterns of complex natural systems in order to bring their most desirable features to computational systems. Thus, the promise of nature-inspired coordination models is to prove themselves fundamental in the design of complex computational systems|such as intelligent, knowledge-intensive, pervasive, adaptive, and self-organising ones. In this paper, we survey the most relevant nature-inspired coordination models in the literature, focussing in particular on tuple-based models, and foresee the most interesting research trends in the field

Efficiently detecting switches against non-stationary opponents

Interactions in multiagent systems are generally more complicated than single agent ones. Game theory provides solutions on how to act in multiagent scenarios; however, it assumes that all agents will act rationally. Moreover, some works also assume the opponent will use a stationary strategy. These assumptions usually do not hold in real world scenarios where agents have limited capacities and may deviate from a perfect rational response. Our goal is still to act optimally in these cases by learning the appropriate response and without any prior policies on how to act. Thus, we focus on the problem when another agent in the environment uses different stationary strategies over time. This will turn the problem into learning in a non-stationary environment, posing a problem for most learning algorithms. This paper introduces DriftER, an algorithm that (1) learns a model of the opponent, (2) uses that to obtain an optimal policy and then (3) determines when it must re-learn due to an opponent strategy change. We provide theoretical results showing that DriftER guarantees to detect switches with high probability. Also, we provide empirical results showing that our approach outperforms state of the art algorithms, in normal form games such as prisoner’s dilemma and then in a more realistic scenario, the Power TAC simulator

From Physical to Virtual: Widening the Perspective on Multi-Agent Environments

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-23850-0_9Since more than a decade, the environment is seen as a key element when analyzing, developing or deploying Multi-Agent Systems (MAS) applications. Especially, for the development of multi-agent platforms it has become a key concept, similarly to many application in the area of location-based, distributed systems. An emerging, prominent application area for MAS is related to Virtual Environments. The underlying technology has evolved in a way, that these applications have grown out of science fiction novels till research papers and even real applications. Even more, current technologies enable MAS to be key components of such virtual environments. In this paper, we widen the concept of the environment of a MAS to encompass new and mixed physical, virtual, simulated, etc. forms of environments. We analyze currently most interesting application domains based on three dimensions: the way different "realities" are mixed via the environment, the underlying natures of agents, the possible forms and sophistication of interactions. In addition to this characterization, we discuss how this widened concept of possible environments influences the support it can give for developing applications in the respective domains.Carrascosa Casamayor, C.; Klugl, F.; Ricci, A.; Boissier, O. (2015). From Physical to Virtual: Widening the Perspective on Multi-Agent Environments. En Agent Environments for Multi-Agent Systems IV. 4th International Workshop, E4MAS 2014 - 10 Years Later, Paris, France, May 6, 2014. 133-146. https://doi.org/10.1007/978-3-319-23850-0_9S133146Aggarwal, J.K., Ryoo, M.S.: Human activity analysis: a review. ACM Comput. 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Agents and Ambient Intelligence, Ambient Intelligence and Smart Environments, pp. 17–31. IOS Press, Amsterdam (2012)Ferber, J.: Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence. Addison Wesley Longman, Harlow (1999)Gelernter, D.: Mirror Worlds - or the Day Software Puts the Universe in a Shoebox: How it Will Happen and What it Will Mean. Oxford University Press, New York (1992)Gibson, W.: Neuromancer. Ace, New York (1984)Klügl, F., Fehler, M., Herrler, R.: About the role of the environment in multi-agent simulations. In: Weyns, D., Van Parunak, H.D., Michel, F. (eds.) E4MAS 2004. LNCS (LNAI), vol. 3374, pp. 127–149. Springer, Heidelberg (2005)Krueger, M.: Artificial Reality II. Addison-Wesley, New York (1991)Luck, M., Aylett, R.: Applying artificial intelligence to virtual reality: intelligent virtual environments. Appl. Artif. 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Agent Oriented Software Engineering (AOSE) Approach to Game Development Methodology

This thesis investigates existing game development methodologies, through the process of researching game and system development models. The results indicate that these methodologies are engineered to solve specific problems, and most are suitable only for specific game genres. Different approaches to building games have been proposed in recent years. However, most of these methodologies focus on the design and implementation phase. This research aims to enhance game development methodologies by proposing a novel game development methodology, with the ability to function in generic game genres, thereby guiding game developers and designers from the start of the game development phase to the end of the implementation and testing phase. On a positive note, aligning development practice with universal standards makes it far easier to incorporate extra team members at short notice. This increased the confidence when working in the same environment as super developers. In the gaming industry, most game development proceeds directly from game design to the implementation phase, and the researcher observes that this is the only industry in which this occurs. It is a consequence of the game industry’s failure to integrate with modern development techniques. The ultimate aim of this research to apply a new game development methodology using most game elements to enhance success. This development model will align with different game genres, and resolve the gap between industry and research area, so that game developers can focus on the important business of creating games. The primary aim of Agent Oriented Agile Base (AOAB) game development methodology is to present game development techniques in sequential steps to facilitate game creation and close the gap in the existing game development methodologies. Agent technology is used in complex domains such as e-commerce, health, manufacturing, games, etc. In this thesis we are interested in the game domain, which comprises a unique set of characteristics such as automata, collaboration etc. Our AOAB will be based on a predictive approach after adaptation of MaSE methodology, and an adaptive approach using Agile methodology. To ensure proof of concept, AOAB game development methodology will be evaluated against industry principles, providing an industry case study to create a driving test game, which was the problem motivating this research. Furthermore, we conducted two workshops to introduce our methodology to both academic and industry participants. Finally, we prepared an academic experiment to use AOAB in the academic sector. We have analyzed the feedbacks and comments and concluded the strengths and weakness of the AOAB methodology. The research achievements are summarized and proposals for future work outlined

Improving water network management by efficient division into supply clusters

El agua es un recurso escaso que, como tal, debe ser gestionado de manera eficiente. Así, uno de los propósitos de dicha gestión debiera ser la reducción de pérdidas de agua y la mejora del funcionamiento del abastecimiento. Para ello, es necesario crear un marco de trabajo basado en un conocimiento profundo de la redes de distribución. En los casos reales, llegar a este conocimiento es una tarea compleja debido a que estos sistemas pueden estar formados por miles de nodos de consumo, interconectados entre sí también por miles de tuberías y sus correspondientes elementos de alimentación. La mayoría de las veces, esas redes no son el producto de un solo proceso de diseño, sino la consecuencia de años de historia que han dado respuesta a demandas de agua continuamente crecientes con el tiempo. La división de la red en lo que denominaremos clusters de abastecimiento, permite la obtención del conocimiento hidráulico adecuado para planificar y operar las tareas de gestión oportunas, que garanticen el abastecimiento al consumidor final. Esta partición divide las redes de distribución en pequeñas sub-redes, que son virtualmente independientes y están alimentadas por un número prefijado de fuentes. Esta tesis propone un marco de trabajo adecuado en el establecimiento de vías eficientes tanto para dividir la red de abastecimiento en sectores, como para desarrollar nuevas actividades de gestión, aprovechando esta estructura dividida. La propuesta de desarrollo de cada una de estas tareas será mediante el uso de métodos kernel y sistemas multi-agente. El spectral clustering y el aprendizaje semi-supervisado se mostrarán como métodos con buen comportamiento en el paradigma de encontrar una red sectorizada que necesite usar el número mínimo de válvulas de corte. No obstante, sus algoritmos se vuelven lentos (a veces infactibles) dividiendo una red de abastecimiento grande.Herrera Fernández, AM. (2011). Improving water network management by efficient division into supply clusters [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/11233Palanci

Swarm-inspired solution strategy for the search problem of unmanned aerial vehicles

Learning from the emergent behaviour of social insects, this research studies the influences of environment to collective problem-solving of insect behaviour and distributed intelligent systems. Literature research has been conducted to understand the emergent paradigms of social insects, and to investigate current research and development of distributed intelligent systems. On the basis of the literature investigation, the environment is considered to have significant impact on the effectiveness and efficiency of collective problem-solving. A framework of collective problem-solving is developed in an interdisciplinary context to describe the influences of the environment to insect behaviour and problem-solving of distributed intelligent systems. The environment roles and responsibilities are transformed into and deployed as a problem-solving mechanism for distributed intelligent systems. A swarm-inspired search strategy is proposed as a behaviour-based cooperative search solution. It is applied to the cooperative search problem of Unmanned Aerial Vehicles (UAVs) with a series of experiments implemented for evaluation. The search environment represents the specification and requirements of the search problem; defines tasks to be achieved and maintained; and it is where targets are locally observable and accessible to UAVs. Therefore, the information provided through the search environment is used to define rules of behaviour for UAVs. The initial detection of target signal refers to modified configurations of the search environment, which mediates local communications among UAVs and is used as a means of coordination. The experimental results indicate that, the swarm-inspired search strategy is a valuable alternative solution to current approaches of cooperative search problem of UAVs. In the proposed search solution, the diagonal formation of two UAVs is able to produce superior performance than the triangular formation of three UAVs for the average detection time and the number of targets located within the maximum time length

Modelação e validação de processos de car-following em Netlogo para simulação de fluxo de tráfego rodoviário

O problema do tráfego rodoviário tem vindo a assumir uma crescente importância devido aos seus efeitos negativos na sociedade moderna, capazes de originar a diminuição da produtividade, da qualidade de vida e a degradação do meio ambiente. No domínio da simulação social, o investimento em simuladores baseados em agentes capazes de analisar os fenómenos de tráfego rodoviário tem aumentado. Uma das áreas fundamentais no estudo de modelos de tráfego é o fluxo gerado pela interacção dos veículos. Este processo designa-se car-following. Com o objectivo de aprofundar a integração de algoritmos de car-following em plataformas e ambientes de simulação social, este trabalho analisa, estende e implementa dois algoritmos de car-following no ambiente Netlogo. Os dois algoritmos baseiam-se em abordagens distintas: um inspirado por sistemas multiagente, baseado em estados cognitivos e regras de decisão; e outro baseado na dinâmica de posição e da velocidade dos veículos. Os dois algoritmos são analisados comparativamente, destacando-se os seus pontos fortes, pontos fracos e a sua validade. Os resultados obtidos validam de diferentes maneiras o impacto dos comportamentos produzidos no fluxo de tráfego e sugerem que o algoritmo inspirado em sistemas multiagente aparenta produzir comportamentos mais realistas.The problem of road traffic has been assuming a growing importance due to its negative effects on modern society, which can lead to lower productivity, declining of quality of life and environmental degradation. In the area of social simulation the investm ent in agent-based simulators, capable of analysing these phenomena, has been increased. One of the key areas in the study of traffic road models is the flow generated by the interaction of vehicles. This process is called car-following. In order to deepen the integration of car-following algorithms across platforms and social simulation environments, this work analyses, extends and implements two car-following algorithms in Netlogo. These algorithms are based on different approaches: one inspired by multi-agent systems, based on decision-rules and cognitive states; and another based on the dynamics of position and vehicle speed. Both algorithms are analysed and compared, highlighting their strengths, weaknesses and its validity. The results authenticate the impact of behaviours produced in the flow of traffic in different ways and suggests that the algorithm based on multi-agent systems seems to produce more realistic behaviour

Urban segregation as a complex system : an agent-based simulation approach

Urban segregation represents a significant barrier for achieving social inclusion in cities. To overcome this, it is necessary to implement policies founded upon a better understanding of segregation dynamics. However, a crucial challenge for achieving such understanding lies in the fact that segregation is a complex system. It emerges from local interactions able to produce unexpected and counterintuitive outcomes that cannot be defined a priori. This study adopts an agent-based simulation approach that addresses the complex nature of segregation. It proposes a model named MASUS, Multi-Agent Simulator for Urban Segregation, which provides a virtual laboratory for exploring theoretical issues and policy approaches concerning segregation. The MASUS model was first implemented for São José dos Campos, a medium-sized Brazilian city. Based on the data of this city, the model was parameterized and calibrated. The potential of MASUS is demonstrated through three different sets of simulation experiments. The first compares simulated data with real data, the second tests theories about segregation, and the third explores the impact of anti-segregation policies. The first set of experiments provides a retrospective validation of the model by simulating the segregation dynamics of São José dos Campos during the period 1991-2000. In general, simulated and real data reveal the same trends, a result that demonstrates that the model is able to accurately represent the segregation dynamics of the study area. The second set of experiments aims at demonstrating the potential of the model to explore and test theoretical issues about urban segregation. These experiments explore the impact of two mechanisms on segregation: income inequality and personal preferences. To test the impact of income inequality, scenarios considering different income distributions were simulated and compared. The results show how decreasing levels of income inequality promote the spatial integration of different social groups in the city. Additional tests were conducted to explore how the preferences of high-income families regarding the presence of other income groups could affect segregation patterns. The results reveal that the high levels of segregation were maintained even in a scenario where affluent households did not take into account the income composition of neighborhoods when selecting their residential location. Finally, the third set of experiments provides new insights about the impact of different urban policies on segregation. One experiment tests whether the regularization of clandestine settlements and equitable distribution of infrastructure would affect the segregation trends in the city. The simulated outputs indicate that they had no significant impact on the segregation patterns. Besides this test focusing on a general urban policy, two specific social-mix policy approaches were explored: poverty dispersion and wealth dispersion. The results suggest that policies based on poverty dispersion, which have been adopted in cities in Europe and the United States, are less effective in developing countries, where poor families represent a large share of the population. On the other hand, the policy based on wealth dispersion was able to produce substantial and long-term improvements in the segregation patterns of the city.Städtische Segregation als komplexes System : Ein agentenbasierter Simulationsansatz Die städtische Segregation stellt eine bedeutende Barriere für die Erreichung der sozialen Inclusion in den Städten dar. Um diese zu überwinden, ist es notwendig, eine Politik zu betreiben, die die Dynamiken der Segregation besser versteht und berücksichtigt. Eine besondere Herausforderung für ein besseres Verständnis dieser Dynamik ist die Tatsache, dass Segregation ein komplexes System ist. Dieses System entsteht aus lokalen Interaktionen, die zu unerwarteten und nicht eingängigen Ergebnissen führt, die nicht von vornherein bestimmt werden können. Diese Studie wendet einen multi-agenten Simulationsmodel an, das die komplexe Natur der Segregation berücksichtigt. Es schlägt ein Modell mit dem Namen MASUS (Multi-Agent Simulator for Urban Segregation) vor. Dieses bietet ein virtuelles Labor für die Untersuchung der theoretischen Aspekte und Politikansätze der Segregation. Das Modell wurde für São José dos Campos, eine mittelgroße brasilianische Stadt, eingesetzt. Das Modell wurde auf der Grundlage der Daten dieser Stadt parametisiert und kallibriert. Das Potenzial von MASUS wird durch drei verschiedene Arten von Simulationsexperimente dargestellt. Die erste vergleicht simulierte Daten mit realen Daten, die zweite prüft Segregationstheorien, und die dritte untersucht die Auswirkungen von Antisegregationspolitik. Die erste Gruppe von Experimenten liefert eine rückblickende Validierung des Modells durch die Simulation der Segregationsdynamiken von São José dos Campos im Zeitraum 1991-2000. Die simulierten und realen Daten zeigen im Allgemeinen die gleichen Trends. Dies zeigt, dass das Modell in der Lage ist, die Segregationsdynamik im Untersuchungsgebiet korrekt darzustellen. Die zweite Gruppe von Experimenten hat zum Ziel, das Potenzial des Modells hinsichtlich der Untersuchung und Prüfung der theoretischen Aspekte städtischer Segregation darzustellen. Diese Experimente untersuchen die Auswirkung von zwei Mechanismen auf Segregation: Einkommensungleichheit und persönliche Präferenzen. Um die Auswirkungen von Einkommensungleichheit zu prüfen, wurden Szenarien mit unterschiedlichen Einkommensverteilungen simuliert und verglichen. Die Ergebnisse zeigen wie abnehmende Einkommenshöhen die räumliche Integration von verschiedenen sozialen Gruppen in der Stadt fördern. Zusätzliche Tests wurden durchgeführt, um zu untersuchen wie die Präferenzen von Haushalten mit hohen Einkommen im Bezug auf das Vorhandensein anderer Einkommensgruppen die Segregationsmuster beeinflussen könnten. Die Ergebnisse zeigen, dass die Segregation auf hohem Niveau blieb sogar in einem Szenario wo wohlhabende Haushalte das Einkommensgefüge der Nachbarschaft bei der Wahl ihrer Wohngegend nicht berücksichtigten. Die dritte Gruppe von Experimenten führt zu neuen Einsichten über die Auswirkungen von verschiedenen städtischen politischen Maßnahmen auf die Segregation. Ein Experiment prüft ob die Regulierung von illegalen Siedlungen und die gleichmäßige Verteilung der Infrastruktur die Segregationstrends in der Stadt beeinflussen. Die Ergebnisse der Simulation zeigen, dass diese keine signifikante Auswirkung auf die Segregationsmuster haben. Neben diesem Test, der die allgemeine städtische Politik zum Inhalt hat, wurden zwei Ansätze der spezifischen Sozialen-Mix-Politik untersucht: Armutsverteilung und Wohlstandsverteilung. Die Ergebnisse deuten daraufhin, dass eine Politik der Armutsverteilung, die aus europäischen und nordamerikanischen Städten bekannt ist, weniger wirkungsvoll in Entwicklungsländern ist, wo arme Familien einen Großteil der Bevölkerung darstellen. Auf der anderen Seite führte eine Politik der Wohlstandsverteilung zu erheblichen und langfristigen Verbesserungen der Segregationsmuster der Stadt