Proceedings of the 11th European Agent Systems Summer School Student Session

This volume contains the papers presented at the Student Session of the 11th European Agent Systems Summer School (EASSS) held on 2nd of September 2009 at Educatorio della Providenza, Turin, Italy. The Student Session, organised by students, is designed to encourage student interaction and feedback from the tutors. By providing the students with a conference-like setup, both in the presentation and in the review process, students have the opportunity to prepare their own submission, go through the selection process and present their work to each other and their interests to their fellow students as well as internationally leading experts in the agent field, both from the theoretical and the practical sector. Table of Contents: Andrew Koster, Jordi Sabater Mir and Marco Schorlemmer, Towards an inductive algorithm for learning trust alignment . . . 5; Angel Rolando Medellin, Katie Atkinson and Peter McBurney, A Preliminary Proposal for Model Checking Command Dialogues. . . 12; Declan Mungovan, Enda Howley and Jim Duggan, Norm Convergence in Populations of Dynamically Interacting Agents . . . 19; Akın Günay, Argumentation on Bayesian Networks for Distributed Decision Making . . 25; Michael Burkhardt, Marco Luetzenberger and Nils Masuch, Towards Toolipse 2: Tool Support for the JIAC V Agent Framework . . . 30; Joseph El Gemayel, The Tenacity of Social Actors . . . 33; Cristian Gratie, The Impact of Routing on Traffic Congestion . . . 36; Andrei-Horia Mogos and Monica Cristina Voinescu, A Rule-Based Psychologist Agent for Improving the Performances of a Sportsman . . . 39; --Autonomer Agent,Agent,Künstliche Intelligenz

A Review of Platforms for the Development of Agent Systems

Agent-based computing is an active field of research with the goal of building autonomous software of hardware entities. This task is often facilitated by the use of dedicated, specialized frameworks. For almost thirty years, many such agent platforms have been developed. Meanwhile, some of them have been abandoned, others continue their development and new platforms are released. This paper presents a up-to-date review of the existing agent platforms and also a historical perspective of this domain. It aims to serve as a reference point for people interested in developing agent systems. This work details the main characteristics of the included agent platforms, together with links to specific projects where they have been used. It distinguishes between the active platforms and those no longer under development or with unclear status. It also classifies the agent platforms as general purpose ones, free or commercial, and specialized ones, which can be used for particular types of applications.Comment: 40 pages, 2 figures, 9 tables, 83 reference

Software Agent Architecture for Managing Inter-Organizational Collaborations

The growing importance of cooperation among organizations, as a result of globalization, current market opportunities and technological advances, encourages organizations to dynamically establish inter-organizational collaborations. These collaborations are carried out by executing collaborative business processes among the organizations. In this work we propose an agent-based software architecture for managing inter-organizational collaborations. Two types of agents are provided: the Collaboration Administrator Agent and the Process Administrator Agent. The former allows organizations setting up collaborations. The latter allows organizations executing collaborative business processes. A Colored Petri Net model specifying the role, which an organization fulfills in a collaborative process, is used to carry out the behavior of the Process Administrator Agent that represents the organization. Planning and execution of the actions of the Process Administrator Agents are driven by a Colored Petri Net machine embedded to them. Thus, Process Administrator Agents do not require to have defined at design-time the protocols they can support. In addition, we propose a model-driven development method for generating Colored Petri Net models from a collaborative process model defined as interaction protocol. Finally, an implementation of the agent-based software architecture and methods based on model-driven development are presented.La creciente importancia de la cooperación entre las organizaciones, como consecuencia de la globalización, las oportunidades actuales de mercado y los avances tecnológicos, alienta a las organizaciones a establecer en forma dinámica colaboraciones inter-organizacionales. Estas colaboraciones se llevan a cabo mediante la ejecución de procesos de negocio colaborativos entre las organizaciones. En este trabajo de investigación se propone una arquitectura basada en agentes de software para la gestión de colaboraciones inter-organizacionales. La arquitectura provee dos tipos de agentes: el Agente Administrador de Colaboraciones y el Agente Administrador de Proceso. El primer agente permite a las organizaciones a establecer colaboraciones. El segundo agente habilita a las organizaciones ejecutar procesos de negocio colaborativos. El rol que una organización desempeña en un proceso colaborativo es especificado mediante un modelo de redes de Petri coloreadas. Este modelo es usado para dirigir el comportamiento del Agente Administrador de Proceso, el cual representa a una organización. La ejecución de los planes y las acciones del Agente Administrador de Proceso son dirigidas mediante una máquina de redes de Petri coloreadas embebida en el agente. Entonces, los Agentes Administrador de Proceso no requieren tener definido en tiempo de diseño los protocolos que dan soporte a su comportamiento. Adicionalmente, se propone un método basado en el desarrollo dirigido por modelos para la generación en forma automática de modelos de redes de Petri coloreadas a partir de un modelo de procesos de negocio colaborativo definido como protocolo de interacción. Finalmente, la implementación de la arquitectura y los métodos basados en el desarrollo dirigido por modelos son presentados.Fil: Tello Leal, Edgar. Universidad Autónoma de Tamaulipas; MéxicoFil: Chiotti, Omar Juan Alfredo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo y Diseño (i); ArgentinaFil: Villarreal, Pablo David. Universidad Tecnologica Nacional. Facultad Regional Santa Fe. Centro de Investigacion y Desarrollo de Ingenieria En Sistemas de Informacion; Argentin

Middle-out domain-specific aspect languages and their application in agent-based modelling runtime inspection

Domain-Specific Aspect Languages (DSALs) are a valuable tool for separating cross-cutting concerns, particularly within fields with endemic cross-cutting practices. Agent-Based Modelling (ABM) runtime inspection, which cuts across the core concern of model development, serves as a prime example. Despite their usefulness, DSALs face multiple adoption issues: the literature regarding their development and use is incohesive, coupling to a weave target hinders re-use, and available tooling is immature compared to Domain-Specific Languages (DSLs). We believe these issues can be aided by furthering DSL middle-out techniques for DSALs.We first define the background of what a DSAL is and how they may be used, moving onto how we can use DSL techniques to further DSALs. We develop a middle-out semantic model approach for developing domain-level DSALs with transparent aspect orientation using adaptions of DSL techniques. We have implemented the approach for model-specific DSALs for the in-house framework Animaux, and as middleware-specific DSAL for agent messages in the JADE framework, which can be specialised to models using extension DSALs. We give illustrative result cases using our implementations to provide a base of the user development costs and performance of this approach.In conclusion, we believe the adoption of these technologies aids ABM applications and encourage future work in similar fields. This thesis has given a base philosophy toward DSLs, a novel approach for the development of middle-out DSALs and illustrative cases of this approach

Modelling water allocation in community irrigation using multi-agent system : A thesis submitted in partial fulfilment of the requirements for the Degree of Doctor of Philosophy at Lincoln University

Insufficient water for irrigation is a common problem in New Zealand, particularly in the Canterbury region, where the use and demand have been steadily increasing over the past 20 years (PCE, 2004; The Parliamentary Commissioner for the Environment, 2004). As a limited resource, there are restrictions around its use. While farmers who need water for irrigation can apply for consent through Environment Canterbury, the process takes a long time and is expensive. As a result, only those with large farms or those who will be able to realise greater financial benefits and higher levels of productivity tend to apply. Instead, most farmers apply to a community irrigation scheme such as Central Plain Water Limited (CPWL) who sells water to individual farmers. As a farmer must pay for each unit of water that s/he uses, s/he needs to have a good irrigation plan in place to ensure they obtain the maximum profit from their investment. In New Zealand, most farmers use computer programmes to estimate their irrigation requirements. The two most common programmes in New Zealand are IrriCalc and OVERSEER. However, both have some limitations: they can only be used to calculate the water needs of an individual farm and neither can prioritise crop water needs during periods of water scarcity. To deal with this problem, we designed an agent-based irrigation management system that can be used to optimise water allocation around the farm which is particularly useful during periods of water scarcity by taking into account the crop types and prioritising them based on the crop utility value. As it calculates the water savings based on each crop’s growth stage and prioritises it in terms of its potential sales price, this agent-based system provides a way to increase farmers’ profitability and to enables them to thrive during periods of water scarcity. During the water reduction exercise, most farms suffer from water shortages. However, there are farmers (who may have overestimated their water needs) who will have excess water. Recognising this situation, we developed a multi-agent system to improve water allocation within a community of water users (where each individual agent represents a farm) and investigated the efficiency of water distribution mechanisms among farms. Farmers can use the proposed multi-agent water management system to negotiate with each other to buy and sell water among themselves. One of the most well-known and simplest methods to achieve this is by using an auction. The choice of an auction was deliberate as it allows agents to buy water at a price, they are comfortable with. An agent must consider how much they are willing to pay for a specific volume of water to ensure their farm remains profitable. This study considered three-auction types and compared the results of each auction in terms of fair water distribution, profit for the sellers and reductions in losses for bidders. We found that the pay-per-bid auctions (discriminatory and uniform) are the best strategies for water distribution that balance between water distribution and gaining profit in water community. In addition, we also investigated how varying behaviours of sellers and buyer affect the outcome of the auction

Desen: Specification of Sociotechnical Systems via Patterns of Regulation and Control

We address the problem of engineering a sociotechnical system (STS) with respect to its stakeholders’ requirements. We motivate a two-tier STS conception comprising a technical tier that provides control mechanisms and describes what actions are allowed by the software components, and a social tier that characterizes the stakeholders’ expectations of each other in terms of norms. We adopt agents as computational entities, each representing a different stakeholder. Unlike previous approaches, our framework, Desen, incorporates the social dimension into the formal verification process. Thus, Desen supports agents potentially violating applicable norms—a consequence of their autonomy. In addition to requirements verification, Desen supports refinement of STS specifications via design patterns to meet stated requirements. We evaluate Desen at three levels. We illustrate how Desen carries out refinement via the application of patterns on a hospital emergency scenario. We show via a human-subject study that a design process based on our patterns is helpful for participants who are inexperienced in conceptual modeling and norms. We provide an agent-based environment to simulate the hospital emergency scenario to compare STS specifications (including participant solutions from the human-subject study) with metrics indicating social welfare and norm compliance, and other domain dependent metrics