Oversight of reorganization in massive multiagent systems

Abstract. We have explored mechanisms for converting organizations to an edge type organization. Beyond structural differences, organizations differ in information flow network and information sharing strategies. We review organizational adaptation. A model of computational organization and reorganization is presented using dynamic roles. In addition to self-organization, our model allows human oversight and guided reorganization. This article lays a foundation for automatic organizational adaptation and human supervision. Our model is exemplified with simulated soccer

Reorganization in Dynamic Agent Societies

En la nueva era de tecnologías de la información, los sistemas tienden a ser cada vez más dinámicos, compuestos por entidades heterogéneas capaces de entrar y salir del sistema, interaccionar entre ellas, y adaptarse a las necesidades del entorno. Los sistemas multiagente han contribuído en los ultimos años, a modelar, diseñar e implementar sistemas autónomos con capacidad de interacción y comunicación. Estos sistemas se han modelado principalmente, a través de sociedades de agentes, las cuales facilitan la interación, organización y cooperación de agentes heterogéneos para conseguir diferentes objetivos. Para que estos paradigmas puedan ser utilizados para el desarrollo de nuevas generaciones de sistemas, características como dinamicidad y capacidad de reorganización deben estar incorporadas en el modelado, gestión y ejecución de estas sociedades de agentes. Concretamente, la reorganización en sociedades de agentes ofrece un paradigma para diseñar aplicaciones abiertas, dinámicas y adaptativas. Este proceso requiere determinar las consecuencias de cambiar el sistema, no sólo en términos de los beneficios conseguidos sinó además, midiendo los costes de adaptación así como el impacto que estos cambios tienen en todos los componentes del sistema. Las propuestas actuales de reorganización, básicamente abordan este proceso como respuestas de la sociedad cuando ocurre un cambio, o bien como un mecanismo para mejorar la utilidad del sistema. Sin embargo, no se pueden definir procesos complejos de decisión que obtengan la mejor configuración de los componentes organizacionales en cada momento, basándose en una evaluación de los beneficios que se podrían obtener así como de los costes asociados al proceso. Teniendo en cuenta este objetivo, esta tesis explora el área de reorganización en sociedades de agentes y se centra principalmente, en una propuesta novedosa para reorganización. Nuestra propuesta ofrece un soporte de toma de decisiones que considera cambios en múltiplesAlberola Oltra, JM. (2013). Reorganization in Dynamic Agent Societies [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/19243Palanci

Multi-dimensional adaptation in MAS organizations

© 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Organization adaptation requires determining the consequences of applying changes not only in terms of the benefits provided but also measuring the adaptation costs as well as the impact that these changes have on all of the components of the organization. In this paper, we provide an approach for adaptation in multiagent systems based on a multidimensional transition deliberation mechanism (MTDM). This approach considers transitions in multiple dimensions and is aimed at obtaining the adaptation with the highest potential for improvement in utility based on the costs of adaptation. The approach provides an accurate measurement of the impact of the adaptation since it determines the organization that is to be transitioned to as well as the changes required to carry out this transition. We show an example of adaptation in a service provider network environment in order to demonstrate that the measurement of the adaptation consequences taken by the MTDM improves the organization performance more than the other approaches.Manuscript received January 2, 2012; revised July 26, 2012; accepted August 7, 2012. Date of publication August 31, 2012; date of current version April 16, 2013. This work was supported in part by projects TIN2008-04446 and TIN2009-13839-C03-01. J. M. Alberola received a Grant from Ministerio de Ciencia e Innovacion de Espana (AP2007-00289). This paper was recommended by Associate Editor J. Huang.Alberola Oltra, JM.; Julian Inglada, VJ.; García-Fornes, A. (2013). Multi-dimensional adaptation in MAS organizations. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics. 43(2):622-633. https://doi.org/10.1109/TSMCB.2012.2213592S62263343

REORGANIZATION OF MASSIVE MULTIAGENT SYSTEMS: MOTL/O

MOTL/O embodies the MOTL paradigm and models organizational adaptation. We report progress on developing computational tools for systematically altering organizational components. This adds a novel dimension to MOTL (Hexmoor, et.al., 2008). This extension is necessary to allow communities of agents or robots to reconfigure their organizational structure in response to changes in the environment. Traditional approach of a hierarchical command and control (C2) structure is ineffective (Alberts & Hayes, 2003). Recently, an edge organization has been proposed as a more suitable alternative Command and control structure in the current information age, due to its empowerment of the edge members, better shared awareness among all the members in the organization, interoperability and most importantly, agility and adaptability to dynamic situations (Chang, 2005). We will explore principled mechanisms for converting a hierarchical organization to an edge type organization. Other than structural differences, organizations differ in information flow network and information sharing strategies. We move toward a solution for organizational adaptation. Beyond current project, many other types of organizational adaptation are possible and require much further research that we anticipate for our future work. This task will lay the foundation for automatic organizational adaptation. This report begins by outlining related work and background in section 2. In section 3 w

Challenges for adaptation in agent societies

The final publication is available at Springer via http://dx.doi.org/[insert DOIAdaptation in multiagent systems societies provides a paradigm for allowing these societies to change dynamically in order to satisfy the current requirements of the system. This support is especially required for the next generation of systems that focus on open, dynamic, and adaptive applications. In this paper, we analyze the current state of the art regarding approaches that tackle the adaptation issue in these agent societies. We survey the most relevant works up to now in order to highlight the most remarkable features according to what they support and how this support is provided. In order to compare these approaches, we also identify different characteristics of the adaptation process that are grouped in different phases. Finally, we discuss some of the most important considerations about the analyzed approaches, and we provide some interesting guidelines as open issues that should be required in future developments.This work has been partially supported by CONSOLIDER-INGENIO 2010 under grant CSD2007-00022, the European Cooperation in the field of Scientific and Technical Research IC0801 AT, and projects TIN2009-13839-C03-01 and TIN2011-27652-C03-01.Alberola Oltra, JM.; Julian Inglada, VJ.; García-Fornes, A. (2014). Challenges for adaptation in agent societies. Knowledge and Information Systems. 38(1):1-34. https://doi.org/10.1007/s10115-012-0565-yS134381Aamodt A, Plaza E (1994) Case-based reasoning; foundational issues, methodological variations, and system approaches. AI Commun 7(1):39–59Abdallah S, Lesser V (2007) Multiagent reinforcement learning and self-organization in a network of agents. 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TRAMMAS: Enhancing Communication in Multiagent Systems

Tesis por compendio[EN] Over the last years, multiagent systems have been proven to be a powerful and versatile paradigm, with a big potential when it comes to solving complex problems in dynamic and distributed environments, due to their flexible and adaptive behavior. This potential does not only come from the individual features of agents (such as autonomy, reactivity or reasoning power), but also to their capability to communicate, cooperate and coordinate in order to fulfill their goals. In fact, it is this social behavior what makes multiagent systems so powerful, much more than the individual capabilities of agents. The social behavior of multiagent systems is usually developed by means of high level abstractions, protocols and languages, which normally rely on (or at least, benefit from) agents being able to communicate and interact indirectly. However, in the development process, such high level concepts habitually become weakly supported, with mechanisms such as traditional messaging, massive broadcasting, blackboard systems or ad hoc solutions. This lack of an appropriate way to support indirect communication in actual multiagent systems compromises their potential. This PhD thesis proposes the use of event tracing as a flexible, effective and efficient support for indirect interaction and communication in multiagent systems. The main contribution of this thesis is TRAMMAS, a generic, abstract model for event tracing support in multiagent systems. The model allows all entities in the system to share their information as trace events, so that any other entity which require this information is able to receive it. Along with the model, the thesis also presents an abstract architecture, which redefines the model in terms of a set of tracing facilities that can be then easily incorporated to an actual multiagent platform. This architecture follows a service-oriented approach, so that the tracing facilities are provided in the same way than other traditional services offered by the platform. In this way, event tracing can be considered as an additional information provider for entities in the multiagent system, and as such, it can be integrated from the earliest stages of the development process.[ES] A lo largo de los últimos años, los sistemas multiagente han demostrado ser un paradigma potente y versátil, con un gran potencial a la hora de resolver problemas complejos en entornos dinámicos y distribuidos, gracias a su comportamiento flexible y adaptativo. Este potencial no es debido únicamente a las características individuales de los agentes (como son su autonomía, y su capacidades de reacción y de razonamiento), sino que también se debe a su capacidad de comunicación y cooperación a la hora de conseguir sus objetivos. De hecho, por encima de la capacidad individual de los agentes, es este comportamiento social el que dota de potencial a los sistemas multiagente. El comportamiento social de los sistemas multiagente suele desarrollarse empleando abstracciones, protocolos y lenguajes de alto nivel, los cuales, a su vez, se basan normalmente en la capacidad para comunicarse e interactuar de manera indirecta de los agentes (o como mínimo, se benefician en gran medida de dicha capacidad). Sin embargo, en el proceso de desarrollo software, estos conceptos de alto nivel son soportados habitualmente de manera débil, mediante mecanismos como la mensajería tradicional, la difusión masiva, o el uso de pizarras, o mediante soluciones totalmente ad hoc. Esta carencia de un soporte genérico y apropiado para la comunicación indirecta en los sistemas multiagente reales compromete su potencial. Esta tesis doctoral propone el uso del trazado de eventos como un soporte flexible, efectivo y eficiente para la comunicación indirecta en sistemas multiagente. La principal contribución de esta tesis es TRAMMAS, un modelo genérico y abstracto para dar soporte al trazado de eventos en sistemas multiagente. El modelo permite a cualquier entidad del sistema compartir su información en forma de eventos de traza, de tal manera que cualquier otra entidad que requiera esta información sea capaz de recibirla. Junto con el modelo, la tesis también presenta una arquitectura {abs}{trac}{ta}, que redefine el modelo como un conjunto de funcionalidades que pueden ser fácilmente incorporadas a una plataforma multiagente real. Esta arquitectura sigue un enfoque orientado a servicios, de modo que las funcionalidades de traza son ofrecidas por parte de la plataforma de manera similar a los servicios tradicionales. De esta forma, el trazado de eventos puede ser considerado como una fuente adicional de información para las entidades del sistema multiagente y, como tal, puede integrarse en el proceso de desarrollo software desde sus primeras etapas.[CA] Al llarg dels últims anys, els sistemes multiagent han demostrat ser un paradigma potent i versàtil, amb un gran potencial a l'hora de resoldre problemes complexes a entorns dinàmics i distribuïts, gràcies al seu comportament flexible i adaptatiu. Aquest potencial no és només degut a les característiques individuals dels agents (com són la seua autonomia, i les capacitats de reacció i raonament), sinó també a la seua capacitat de comunicació i cooperació a l'hora d'aconseguir els seus objectius. De fet, per damunt de la capacitat individual dels agents, es aquest comportament social el que dóna potencial als sistemes multiagent. El comportament social dels sistemes multiagent solen desenvolupar-se utilitzant abstraccions, protocols i llenguatges d'alt nivell, els quals, al seu torn, es basen normalment a la capacitat dels agents de comunicar-se i interactuar de manera indirecta (o com a mínim, es beneficien en gran mesura d'aquesta capacitat). Tanmateix, al procés de desenvolupament software, aquests conceptes d'alt nivell son suportats habitualment d'una manera dèbil, mitjançant mecanismes com la missatgeria tradicional, la difusió massiva o l'ús de pissarres, o mitjançant solucions totalment ad hoc. Aquesta carència d'un suport genèric i apropiat per a la comunicació indirecta als sistemes multiagent reals compromet el seu potencial. Aquesta tesi doctoral proposa l'ús del traçat d'esdeveniments com un suport flexible, efectiu i eficient per a la comunicació indirecta a sistemes multiagent. La principal contribució d'aquesta tesi és TRAMMAS, un model genèric i abstracte per a donar suport al traçat d'esdeveniments a sistemes multiagent. El model permet a qualsevol entitat del sistema compartir la seua informació amb la forma d'esdeveniments de traça, de tal forma que qualsevol altra entitat que necessite aquesta informació siga capaç de rebre-la. Junt amb el model, la tesi també presenta una arquitectura abstracta, que redefineix el model com un conjunt de funcionalitats que poden ser fàcilment incorporades a una plataforma multiagent real. Aquesta arquitectura segueix un enfoc orientat a serveis, de manera que les funcionalitats de traça són oferides per part de la plataforma de manera similar als serveis tradicionals. D'aquesta manera, el traçat d'esdeveniments pot ser considerat com una font addicional d'informació per a les entitats del sistema multiagent, i com a tal, pot integrar-se al procés de desenvolupament software des de les seues primeres etapes.Búrdalo Rapa, LA. (2016). TRAMMAS: Enhancing Communication in Multiagent Systems [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/61765TESISCompendi

FATMAS: a methodology to design fault-tolerant multi-agent systems

Un système multi-agent (SMA) est un système dans lequel plusieurs agents opèrent et interagissent. Chaque agent a la responsabilité d’exécuter des tâches. Cependant, chaque agent, pour diverses raisons, peut rencontrer des problèmes pendant l’exécution de ses tâches ; ce qui peut induire un disfonctionnement du SMA. Cependant, le SMA doit être en mesure de détecter les sources de problèms (d’erreurs) afin de les contrôler et ainsi continuer son exécution correctement. Un tel SMA est appelé un SMA tolérant aux fautes. Il existe deux types de sources d’erreurs pour un agent : les erreurs causées par son environnment et les erreurs dûes à sa programmation. Dans la littérature, il existe plusieurs techniques qui traitent des erreurs de programmation au niveau des agents. Cependant, ces techniques ne traitent pas des erreurs causées par l’environnement de l’agent. Tout d’abord, nous distinguons entre l’environnment d’un agent et l’environnement du SMA. L’environnement d’un agent représente toutes les composantes matérielles ou logicielles que l’agent ne peut contrôler mais avec lesquelles il interagit. Cependant, l’environnment du SMA représente toutes les composantes que le système ne contrôle pas mais avec lesquelles il interagit. Ainsi, le SMA peut contrôler certaines des composantes avec lesquelles un agent interagit. Ainsi, une composante peut appartenir à l’environnement d’un agent et ne pas appartenir à l’environnement du système. Dans ce travail, nous présentons une méthodologie de conception de SMA tolérants aux fautes, nommée FATMAS, qui permet au concepteur du SMA de détecter et de corriger, si possible, les erreurs causées par les environnements des agents. Cette méthodologie permettra ainsi de délimiter la frontière du SMA de son environnement avec lequel il interagit. La frontière du SMA est déterminée par les différentes composantes (matérielles ou logicielles) que le système contrôle. Ainsi, le SMA, à l’intérieur de sa frontière, peut corriger les erreurs provenant de ses composantes. Cependant, le SMA n’a aucun contrôle sur toutes les composantes opérant dans son environnement. La méthodologie, que nous proposons, doit couvrir les trois premières phases d’un développement logiciel qui sont l’analyse, la conception et l’implémentation tout en intégrant, dans son processus de développement, une technique permettant au concepteur du système de délimiter la frontière du SMA et ainsi détecter les sources d’erreurs et les contrôler afin que le système multi-agent soit tolérant aux fautes (SMATF). Cependant, les méthodologies de conception de SMA, référencées dans la littérature, n’intègrent pas une telle technique. FATMAS offre au concepteur du SMATF quatre modèles pour décrire et développer le SMA ainsi qu’une technique de réorganisation du système qui lui permet de détecter et de contrôler ses sources d’erreurs, et ainsi définir la frontière du SMA. Chaque modèle est associé à un micro processus qui guide le concepteur lors du développement du modèle. FATMAS offre aussi un macro-processus, qui définit le cycle de développement de la méthodologie. FATMAS se base sur un développement itératif pour identifier et déterminer les tâches à ajouter au système afin de contrôler des sources d’erreurs. À chaque itération, le concepteur évalue, selon une fonction de coût/bénéfice s’il est opportun d’ajouter de nouvelles tâches de contrôle au système. Le premier modèle est le modèle de tâches-environnement. Il est développé lors de la phase d’analyse. Il identifie les différentes tâches que les agents doivent exécuter, leurs préconditions et leurs ressources. Ce modèle permet d’identifier différentes sources de problèmes qui peuvent causer un disfonctionnement du système. Le deuxième modèle est le modèle d’agents. Il est développé lors de la phase de conception. Il décrit les agents, leurs relations, et spécifie pour chaque agent les ressources auxquelles il a le droit d’accéder. Chaque agent exécutera un ensemble de tâches identifiées dans le modèle de tâches-environnement. Le troisième modèle est le modèle d’interaction d’agents. Il est développé lors de la phase de conception. Il décrit les échanges de messages entre les agents. Le quatrième modèle est le modèle d’implémentation. Il est développé lors de la phase d’implémentation. Il décrit l’infrastructure matérielle sur laquelle le SMA va opérer ainsi que l’environnement de développement du SMA. La méthodologie inclut aussi une technique de réorganisation. Cette technique permet de délimiter la frontière du SMA et contrôler, si possible, ses sources d’erreurs. Cette technique doit intégrer trois techniques nécessaires à la conception d’un système tolérant aux fautes : une technique de prévention d’erreurs, une technique de recouvrement d’erreurs, et une technique de tolérance aux fautes. La technique de prévention d’erreurs permet de délimiter la frontière du SMA. La technique de recouvrement d’erreurs permet de proposer une architecture du SMA pour détecter les erreurs. La technique de tolérance aux fautes permet de définir une procédure de réplication d’agents et de tâches dans le SMA pour que le SMA soit tolérant aux fautes. Cette dernière technique, à l’inverse des techniques de tolérance aux fautes existantes, réplique les tâches et les agents et non seulement les agents. Elle permet ainsi de réduire la complexité du système en diminuant le nombre d’agents à répliquer. Résumé iv De même, un agent peut ne pas être en erreur mais la composante matérielle sur laquelle il est exécuté peut ne plus être fonctionnelle. Ce qui constitue une source d’erreurs pour le SMA. Il faudrait alors que le SMA continue à s’exécuter correctement malgrè le disfonctionnement d’une composante. FATMAS fournit alors un support au concepteur du système pour tenir compte de ce type d’erreurs soit en contrôlant les composantes matérielles, soit en proposant une distribution possible des agents sur les composantes matérielles disponibles pour que le disfonctionnement d’une composante matérielle n’affecte pas le fonctionnement du SMA. FATMAS permet d’identifier des sources d’erreurs lors de la phase de conception du système. Cependant, elle ne traite pas des sources d’erreurs de programmation. Ainsi, la technique de réorganization proposée dans ce travail sera validée par rapport aux sources d’erreurs identifiées lors de la phase de conception et provenant de la frontière du SMA. Nous démontrerons formellement que, si une erreur provient d’une composante que le SMA contrôle, le SMA devrait être opérationnel. Cependant, FATMAS ne certifie pas que le futur système sera toujours opérationnel car elle ne traîte pas des erreurs de programmation ou des erreurs causées par son environnement.A multi-agent system (MAS) consists of several agents interacting together. In a MAS, each agent performs several tasks. However, each agent is prone to individual failures so that it can no longer perform its tasks. This can lead the MAS to a failure. Ideally, the MAS should be able to identify the possible sources of failures and try to overcome them in order to continue operating correctly ; we say that it should be fault-tolerant. There are two kinds of sources of failures to an agent : errors originating from the environment with which the agents interacts, and programming exceptions. There are several works on fault-tolerant systems which deals with programming exceptions. However, these techniques does not allow the MAS to identify errors originating from an agent’s environment. In this thesis, we propose a design methodology, called FATMAS, which allows a MAS designer to identify errors originating from agents’ environments. Doing so, the designer can determine the sources of failures it could be able to control and those it could not. Hence, it can determine the errors it can prevent and those it cannot. Consequently, this allows the designer to determine the system’s boundary from its environment. The system boundary is the area within which the decision-taking process of the MAS has power to make things happen, or prevent them from happening.We distinguish between the system’s environment and an agent’s environment. An agent’s environment is characterized by the components (hardware or software) that the agent does not control. However, the system may control some of the agent’s environment components. Consequently, some of the agent’s environment components may not be a part of the system’s environment. The development of a fault-tolerant MAS (FTMAS) requires the use of a methodology to design FTMAS and of a reorganization technique that will allow the MAS designer to identify and control, if possible, different sources of system failure. However, current MAS design methodologies do not integrate such a technique. FATMAS provides four models used to design and implement the target system and a reorganization technique to assist the designer in identifying and controlling different sources of system’s failures. FATMAS also provides a macro process which covers the entire life cycle of the system development as well as several micro processes that guide the designer when developing each model. The macro-process is based on an iterative approach based on a cost/benefit evaluation to help the designer to decide whether to go from one iteration to another. The methodology has three phases : analysis, design, and implementation. The analysis phase develops the task-environment model. This model identifies the different tasks the agents will perform, their resources, and their preconditions. It identifies several possible sources of system failures. The design phase develops the agent model and the agent interaction model. The agent model describes the agents and their resources. Each agent performs several tasks identified in the task-environment model. The agent interaction model describes the messages exchange between agents. The implementation phase develops the implementation model, and allows an automatic code generation of Java agents. The implementation model describes the infrastructure upon which the MAS will operate and the development environment to be used when developing the MAS. The reorganization technique includes three techniques required to design a fault-tolerant system : a fault-prevention technique, a fault-recovery technique, and a fault-tolerance technique. The fault-prevention technique assists the designer in delimiting the system’s boundary. The fault-recovery technique proposes a MAS architecture allowing it to detect failures. The fault-tolerance technique is based on agent and task redundancy. Contrary to existing fault-tolerance techniques, this technique replicates tasks and agents and not only agents. Thus, it minimizes the system complexity by minimizing the number of agents operating in the system. Furthermore, FATMAS helps the designer to deal with possible physical component failures, on which the MAS will operate. It proposes a way to either control these components or to distribute the agents on these components in such a way that if a component is in failure, then the MAS could continue operating properly. The FATMAS methodology presented in this dissertation assists a designer, in its development process, to build fault-tolerant systems. It has the following main contributions : 1. it allows to identify different sources of system failure ; 2. it proposes to introduce new tasks in a MAS to control the identified sources of failures ; 3. it proposes a mechanism which automatically determines which tasks (agents) should be replicated and in which other agents ; 4. it reduces the system complexity by minimizing the replication of agents ; Abstract vii 5. it proposes a MAS reorganization technique which is embedded within the designed MAS and assists the designer to determine the system’s boundary. It proposes a MAS architecture to detect and recover from failures originating from the system boundary. Moreover, it proposes a way to distribute agents on the physical components so that the MAS could continue operating properly in case of a component failure. This could make the MAS more robust to fault prone environments. FATMAS alows to determine different sources of failures of a MAS. The MAS controls the sources of failures situated in its boundary. It does not control the sources of failures situated in its environments. Consequently, the reorganization technique proposed in this dissertation will be proven valid only in the case where the sources of failures are controlled by the MAS. However, it cannot be proven that the future system is fault-tolerant since faults originating from the environment or from coding are not dealt with

Biologically Inspired Near Extinct System Reconstruction

Recovery software system operations from a state of extensive damage without human intervention is a challenging problem as it may need to be based on a different infrastructure from the one that the system was originally designed for and deployed on (i.e., computational and communication devices) and significant reorganization of system functionalities. In this paper, we introduce a bio-inspired approach for reconstructing nearly extinct complex software systems. Our approach is based on encoding a computational DNA (co-DNA) of a system and computational analogues of biological processes to enable the transmission of co-DNA over computational devices and, through it, the transformation of these devices into system cells that can realise chunks of the system functionality, and spread further its reconstruction process

Relationship recommender system in a business and employment-oriented social network

[EN] In the last ten years, social networks have had a great influence on people’s lifestyles and have changed, above all, the way users communicate and relate. This is why, one of the main lines of research in the field of social networks focuses on finding and analyzing possible connections between users. These developments allow users to expand on their network of contacts without having to search among the total set of users. However, there are many types of social networks which attract users with specific needs, these needs influence on the type of contacts users are looking for. Our article proposes a relationship recommender system for a business and employment-oriented social network. The presented system functions by extracting relevant information from the social network which it then uses to adequately recommend new contacts and job offers to users. The recommender system uses information gathered from job offer descriptions, user profiles and users’ actions. Then, different metrics are applied in order to discover new ties that are likely to convert into relationships