Augmenting Agent Platforms to Facilitate Conversation Reasoning

Within Multi Agent Systems, communication by means of Agent Communication Languages (ACLs) has a key role to play in the co-operation, co-ordination and knowledge-sharing between agents. Despite this, complex reasoning about agent messaging, and specifically about conversations between agents, tends not to have widespread support amongst general-purpose agent programming languages. ACRE (Agent Communication Reasoning Engine) aims to complement the existing logical reasoning capabilities of agent programming languages with the capability of reasoning about complex interaction protocols in order to facilitate conversations between agents. This paper outlines the aims of the ACRE project and gives details of the functioning of a prototype implementation within the Agent Factory multi agent framework

Automated Negotiation for Provisioning Virtual Private Networks Using FIPA-Compliant Agents

This paper describes the design and implementation of negotiating agents for the task of provisioning virtual private networks. The agents and their interactions comply with the FIPA specification and they are implemented using the FIPA-OS agent framework. Particular attention is focused on the design and implementation of the negotiation algorithms

Issues in integrating existing multi-agent systems for power engineering applications

Multi-agent systems (MAS) have proven to be an effective platform for diagnostic and condition monitoring applications in the power industry. For example, a multi-agent system architecture, entitled condition monitoring multi-agent system (COMMAS) (McArthur et al., 2004), has been applied to the ultra high frequency (UHF) monitoring of partial discharge activity inside transformers. Additionally, a multi-agent system, entitled protection engineering diagnostic agents (PEDA) (Hossack et al., 2003), has demonstrated the use of MAS technology for automated and enhanced post-fault analysis of power systems disturbances based on SCADA and digital fault recorder (DFR) data. In this paper, the authors propose the integration of COMMAS and PEDA as a means of offering enhanced decision support to engineers tasked with managing transformer assets. By providing automatically interpreted data related to condition monitoring and power system disturbances, the proposed integrated system offer engineers a more comprehensive picture of the health of a given transformer. Defects and deterioration in performance can be correlated with the operating conditions it experiences. The integration of COMMAS and PEDA has highlighted the issues inherent to the inter-operation of existing multi-agent systems and, in particular, the issues surrounding the use of differing ontologies. The authors believe that these issues need to be addressed if there is to be widespread deployment of MAS technology within the power industry. This paper presents research undertaken to integrate the two MAS and to deal with ontology issues

Towards engineering ontologies for cognitive profiling of agents on the semantic web

Research shows that most agent-based collaborations suffer from lack of flexibility. This is due to the fact that most agent-based applications assume pre-defined knowledge of agents’ capabilities and/or neglect basic cognitive and interactional requirements in multi-agent collaboration. The highlight of this paper is that it brings cognitive models (inspired from cognitive sciences and HCI) proposing architectural and knowledge-based requirements for agents to structure ontological models for cognitive profiling in order to increase cognitive awareness between themselves, which in turn promotes flexibility, reusability and predictability of agent behavior; thus contributing towards minimizing cognitive overload incurred on humans. The semantic web is used as an action mediating space, where shared knowledge base in the form of ontological models provides affordances for improving cognitive awareness

Agent oriented modeling of business information systems

Enterprise modeling is an abstract definition of processes running in enterprise using process, value, data and resource models. There are two perspectives of business modeling: process perspective and value chain perspective. Both have some advantages and disadvantages. This paper proposes a combination of both perspectives into one generic model. The model takes also social part or the enterprise system into consideration and pays attention to disturbances influencing the enterprise system. Due to heterogeneous nature of the enterprise processes the outline proposed is oriented on the modeling using agents. Several types of agents are defined for the simulation model. The agents are structured into several layers. Well known JADE platform is proposed as the modeling framework. Further research directions are summed up in conclusionprocess model, value chain model, business pattern, agent, control loop, feedback, JADE platform.

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