Talking Helps: Evolving Communicating Agents for the Predator-Prey Pursuit Problem

We analyze a general model of multi-agent communication in which all agents communicate simultaneously to a message board. A genetic algorithm is used to evolve multi-agent languages for the predator agents in a version of the predator-prey pursuit problem. We show that the resulting behavior of the communicating multi-agent system is equivalent to that of a Mealy finite state machine whose states are determined by the agents’ usage of the evolved language. Simulations show that the evolution of a communication language improves the performance of the predators. Increasing the language size (and thus increasing the number of possible states in the Mealy machine) improves the performance even further. Furthermore, the evolved communicating predators perform significantly better than all previous work on similar preys. We introduce a method for incrementally increasing the language size which results in an effective coarse-to-fine search that significantly reduces the evolution time required to find a solution. We present some observations on the effects of language size, experimental setup, and prey difficulty on the evolved Mealy machines. In particular, we observe that the start state is often revisited, and incrementally increasing the language size results in smaller Mealy machines. Finally, a simple rule is derived that provides a pessimistic estimate on the minimum language size that should be used for any multi-agent problem

Estudio de la influencia de topologías de comunicación en sistemas multiagente bioinspirados

Máster en Ingeniería en Informática y de Telecomunicacione

Smart grids as distributed learning control

The topic of smart grids has received a lot of attention but from a scientific point of view it is a highly imprecise concept. This paper attempts to describe what could ultimately work as a control process to fulfill the aims usually stated for such grids without throwing away some important principles established by the pioneers in power system control. In modern terms, we need distributed (or multi-agent) learning control which is suggested to work with a certain consensus mechanism which appears to leave room for achieving cyber-physical security, robustness and performance goals. © 2012 IEEE.published_or_final_versio

Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: NL

Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: N

Middleware architectures for the smart grid: A survey on the state-of-the-art, taxonomy and main open issues

The integration of small-scale renewable energy sources in the smart grid depends on several challenges that must be overcome. One of them is the presence of devices with very different characteristics present in the grid or how they can interact among them in terms of interoperability and data sharing. While this issue is usually solved by implementing a middleware layer among the available pieces of equipment in order to hide any hardware heterogeneity and offer the application layer a collection of homogenous resources to access lower levels, the variety and differences among them make the definition of what is needed in each particular case challenging. This paper offers a description of the most prominent middleware architectures for the smart grid and assesses the functionalities they have, considering the performance and features expected from them in the context of this application domain

An Agent-Based Approach to Self-Organized Production

The chapter describes the modeling of a material handling system with the production of individual units in a scheduled order. The units represent the agents in the model and are transported in the system which is abstracted as a directed graph. Since the hindrances of units on their path to the destination can lead to inefficiencies in the production, the blockages of units are to be reduced. Therefore, the units operate in the system by means of local interactions in the conveying elements and indirect interactions based on a measure of possible hindrances. If most of the units behave cooperatively ("socially"), the blockings in the system are reduced. A simulation based on the model shows the collective behavior of the units in the system. The transport processes in the simulation can be compared with the processes in a real plant, which gives conclusions about the consequencies for the production based on the superordinate planning.Comment: For related work see http://www.soms.ethz.c

Multi Agent Systems in Logistics: A Literature and State-of-the-art Review

Based on a literature survey, we aim to answer our main question: “How should we plan and execute logistics in supply chains that aim to meet today’s requirements, and how can we support such planning and execution using IT?†Today’s requirements in supply chains include inter-organizational collaboration and more responsive and tailored supply to meet specific demand. Enterprise systems fall short in meeting these requirements The focus of planning and execution systems should move towards an inter-enterprise and event-driven mode. Inter-organizational systems may support planning going from supporting information exchange and henceforth enable synchronized planning within the organizations towards the capability to do network planning based on available information throughout the network. We provide a framework for planning systems, constituting a rich landscape of possible configurations, where the centralized and fully decentralized approaches are two extremes. We define and discuss agent based systems and in particular multi agent systems (MAS). We emphasize the issue of the role of MAS coordination architectures, and then explain that transportation is, next to production, an important domain in which MAS can and actually are applied. However, implementation is not widespread and some implementation issues are explored. In this manner, we conclude that planning problems in transportation have characteristics that comply with the specific capabilities of agent systems. In particular, these systems are capable to deal with inter-organizational and event-driven planning settings, hence meeting today’s requirements in supply chain planning and execution.supply chain;MAS;multi agent systems

Adoption of vehicular ad hoc networking protocols by networked robots

This paper focuses on the utilization of wireless networking in the robotics domain. Many researchers have already equipped their robots with wireless communication capabilities, stimulated by the observation that multi-robot systems tend to have several advantages over their single-robot counterparts. Typically, this integration of wireless communication is tackled in a quite pragmatic manner, only a few authors presented novel Robotic Ad Hoc Network (RANET) protocols that were designed specifically with robotic use cases in mind. This is in sharp contrast with the domain of vehicular ad hoc networks (VANET). This observation is the starting point of this paper. If the results of previous efforts focusing on VANET protocols could be reused in the RANET domain, this could lead to rapid progress in the field of networked robots. To investigate this possibility, this paper provides a thorough overview of the related work in the domain of robotic and vehicular ad hoc networks. Based on this information, an exhaustive list of requirements is defined for both types. It is concluded that the most significant difference lies in the fact that VANET protocols are oriented towards low throughput messaging, while RANET protocols have to support high throughput media streaming as well. Although not always with equal importance, all other defined requirements are valid for both protocols. This leads to the conclusion that cross-fertilization between them is an appealing approach for future RANET research. To support such developments, this paper concludes with the definition of an appropriate working plan

An adaptive communication model for mobile agents in highly dynamic networks based on forming flexible regions via swarming behabiour

Im letzten Jahrzehnt gilt die mobile Agententechnologie als eines der wichtigsten Forschungsgebiete der Informatik. Mobile Agenten sind Software, die Aufträge im Namen ihrer Besitzer erfüllen können (ZK02). Mobile Agenten können selbstbestimmend von Server zu Server migrieren, sie können ihren Arbeitsstand speichern und dann ihre Arbeit am neuen Aufenthaltsort fortsetzen. Ihre wichtigsten Merkmale sind: autonom, reaktiv, opportunistisch und zielgerichtet. Diese genannten Merkmale sind für verteilte Anwendungen geeignet, z. B: Ressourcenverteilung (TYI99), Netzwerkmanagement (MT99), E-Commerce (BGP05), Fernüberwachung CMCV02), Gesundheitssysteme (Mor06), um nur einige zu nennen. Es ist die Mobilität der Agenten, die mobile Agenten zu einer guten Computing Technologie macht (Pau02). Kommunikation ist wesentlich in verteilten Systemen, und dies gilt auch für mobile Agentensysteme (LHL02). Neben den eher technischen Aspekten mobiler Agententechnologien, wie Migration (Bra03) und Kontrollmechanismen (Bau00), wurde die Kommunikation zwischen den Agenten als eine der wichtigsten Komponenten in der mobilen Agententechnologie identifiziert (FLP98). Es ist diskutiert worden, ob Agentenkommunikation ausschließlich lokal sein sollte, angesichts der Tatsache, dass mobile Agenten erfunden wurden, weil man die Verarbeitung zu den Daten tragen möchte, anstatt umgekehrt (SS97). Allerdings hat es sich gezeigt, dass es in vielen Fällen lohnt, wenn die mobilen Agenten kommunizieren anstatt migrieren (BHR+97),(FLP98),(ea02). Kommunikation hilft mobilen Agenten, eine bessere Leistung zu erreichen (Erf04). Kommunikation ist daher aus unserer Sicht die Basis mobiler Agentensysteme. An der Friedrich-Schiller-Universität Jena ist das interdisziplinäre Projekt SpeedUp seit April 2009 durchgeführt worden (FSU11). Das Projekt entwickelt ein Unterstützungssystem für Rettungs- und Einsatzkräfte bei einem Massenanfall von Verletzten (MANV). Im Projekt ist das Konzept mobiler Agenten als eine der Basistechnologien ausgesucht worden. Die hohe Netzwerkdynamik stellt neue Herausforderungen für mobile Agentensysteme dar, die in MANV Rettungsszenarien arbeiten. Es wird erwartet, dass die Kommunikation sich an die dynamische Umgebung zur Ausführungszeit anpassen kann. Dazu fehlen heute tragfähige Konzepte. In dieser Arbeit wird daher ein Ansatz zur adaptiven Kommunikation mobiler Agenten in hochdynamischen Netzwerken des SpeedUp-Typs vorgestellt. Nach unserer Beurteilung sollte die Kommunikation zwischen den mobilen Agenten nicht nur Interoperabilität und Standortunabhängigkeit, sondern auch Anpassungsfähigkeit aufweisen. Wir schlagen ein Kommunikationsmodell vor, das sich auf den koordinierenden Aspekt und das Zusammenspiel der Agenten konzentriert, sowie die Zuverlässigkeit und die Fehlertoleranz unterstützt. Um die Netzwerkdynamik zu managen, planen wir einen selbstorganisierten Mechanismus zu verwenden, der sich ”honey bee” inspiriertes Verfahren nennt. Wir werden dazu eine Software für ein adaptives Kommunikationsmodell mobiler Agenten, basierend auf das mobile Agentensystem Ellipsis gestalten, implementieren, und evaluieren.In the last decade, mobile agent technology has been considered as one of the most active research fields in computer science. Mobile agents are software agents which run on behalf of their owner to fulfil jobs that have been ordered (ZK02). They have the ability to migrate from location to location in the network, they can temporarily save their work state at the time of migrating and then restore their tasks when arriving at the new location. Their outstanding characteristics are to be autonomous, reactive, opportunistic, and goal-oriented. Those characteristics are suitable for distributed applications, such as resource allocation (TYI99), network management (MT99), remote supervision (CMCV02), e-commerce (BGP05), health care systems (Mor06), to name but a few. It is the mobility of mobile agents that makes them to be a powerful computing technique, especially for pervasive computing (Pau02). Communication is an essential component of distributed systems and this is no exception for multiagent systems (LHL02). Besides technical aspects of mobile agent technology, such as migrations (Bra03) and control mechanisms (Bau00), communication between mobile agents has been identified as an important issue in mobile agent technology (FLP98). It has been argued whether agent communication should be remote or restricted to local, considering that the main reason for the birth of mobile agents was to move computation to the data instead of moving the data to the computation. Therefore, remote communication could be avoided completely (SS97). However, it has been shown that in many cases mobile agent systems can benefit from performing communication instead of sending agents to remote platforms (BHR+97),(FLP98),(ea02). The communication between agents helps to increase the chance that an agent attains its objectives (Erf04). Communication is one of the bases of multi-agent systems; it is difficult, if not impossible for a group of agents to solve tasks without communication (Hel03). At Friedrich Schiller University Jena, an interdisciplinary project, named SpeedUp, for the support of handling mass casualty incidents (MCI) has been in development since April 2009 (FSU11). In the project the mobile agent concept has been selected as one of the main technologies on the communication infrastructure level. The dynamic nature of MCI networks poses new challenges to mobile systems working in a rescue scenario. For mobile agent systems working in highly dynamic networks, communication between mobile agents is expected to adapt easily to environmental stimuli which occur at execution time. Much research has been done into the design of an appropriate, highly flexible model for mobile agent communication in dynamic networks. However, to the best of our knowledge none of the suggested solutions has been able to achieve the necessary performance and quality attributes to count as a practical solution. In most cases, these existing approaches seem to neglect the inherent dynamics of modern networks. In this dissertation, we present our approach for an adaptive communication model for mobile agent systems in highly dynamic networks of the SpeedUp type. In our opinion, communication in mobile agent systems should deal not only with interoperability and location-transparency, but also with adaptability. To achieve industrial strength, we propose a model for agent communication that focuses on the cooperation aspect of agent interaction and supports reliability and fault tolerance as the key qualities, while keeping up an acceptable overall performance at the same time. For the management of highly dynamic communication domains we use a self-organizing mechanism, a so-called honey bee inspired algorithm. In order to ensure message delivery, we propose a resilient mechanism for the management of a mobile agent’s location. Based on this thesis, we will design, implement and evaluate a software prototype for an adaptive model for mobile agent communication based on the Ellipsis mobile agent system