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Über dieses Buch

Research on Agents and Multi-Agent Systems has matured during the last decade and many effective applications of this technology are now deployed. PAAMS provides an international forum to present and discuss the latest scientific developments and their effective applications, to assess the impact of the approach, and to facilitate technology transfer. PAAMS started as a local initiative, but has since grown to become THE international yearly platform to present, to discuss, and to disseminate the latest developments and the most important outcomes related to real-world applications. It provides a unique opportunity to bring multi-disciplinary experts, academics and practitioners together to exchange their experience in the development and deployment of Agents and Multi-Agent Systems. PAAMS intends to bring together researchers and developers from industry and the academic world to report on the latest scientific and technical advances on the application of multi-agent systems, to discuss and debate the major issues, and to showcase the latest systems using agent based technology. It will promote a forum for discussion on how agent-based techniques, methods, and tools help system designers to accomplish the mapping between available agent technology and application needs. Other stakeholders should be rewarded with a better understanding of the potential and challenges of the agent-oriented approach.

This edition of PAAMS brings together past experience, current work, and promising future trends associated with distributed computing, artificial intelligence and their application in order to provide efficient solutions to real problems. This symposium is organized by the Bioinformatics, Intelligent System and Educational Technology Research Group (http://bisite.usal.es/) of the University of Salamanca. The present edition will be held in Salamanca, Spain, from 28th to 30th March 2012.

This edition of PAAMS brings together past experience, current work, and promising future trends associated with distributed computing, artificial intelligence and their application in order to provide efficient solutions to real problems. This symposium is organized by the Bioinformatics, Intelligent System and Educational Technology Research Group (http://bisite.usal.es/) of the University of Salamanca. The present edition will be held in Salamanca, Spain, from 28th to 30th March 2012.

Inhaltsverzeichnis

Frontmatter

Language Grid Revisited: An Infrastructure for Intercultural Collaboration

Since various communities withmultiple languagesinteract in daily life, tools are needed to support intercultural communication. However, we often observe that the success of a multi-language tool in one situation does not guarantee its success in another. To develop multi-language environments that can handle various situations in various communities, existing language resources should be easy to share and customize. Therefore, we designed the Language Grid as service-oriented collective intelligence; it allows users to freely create language services from existing language resources and combine them to develop new services to meet their own requirements. This paper explains the design concept and service architecture of the Language Grid, and our approach to user involvement in collective intelligence activities.An institutional design is also essential forcollective intelligence. We create a federated operation model to bridgedifferentstakeholders including service providers, service users, and service grid operators.

Toru Ishida, Yohei Murakami, Donghui Lin, Masahiro Tanaka, Rieko Inaba

An Agent-Based Community to Manage Urban Parking

In the context of road urban traffic management, the problem of parking spots search is a major issue because of its serious economic and ecological fallout. In this paper, we propose a multi-agent system that aims to decrease, for private vehicles drivers, the parking spots search time. In the system that we propose, a community of drivers shares information about spots availability. Our solution has been tested following different configurations. The first results show a decrease in parking spots search time.

Nesrine Bessghaier, Mahdi Zargayouna, Flavien Balbo

Cooperative Ant Colony Optimization in Traffic Route Calculations

Ant Colony Optimization (ACO) algorithms tend to be isolated processes. When applying ACO principles to traffic route calculations, ants exploring the traffic network on behalf of a vehicle typically only perceive and apply pheromones related to that vehicle. Between ants exploring on behalf of different vehicles little cooperation exists. While such cooperation could improve the performance of the ACO algorithm, it is difficult to achieve because ants working on behalf of different vehicles are solving different problems. This paper presents and evaluates a method of cooperation between ants finding routes on behalf of different vehicles by sharing more general knowledge through pheromones. A simulation of the proposed approach is used to evaluate the cooperative ACO algorithm and to compare it with an uncooperative version based on the quality of the calculated routes and the number of iterations needed to find good results. The evaluation indicates that the quality of the solution does not improve and that the speedup is insignificant when using the collaborative variant.

Rutger Claes, Tom Holvoet

Using Agent Satisfiability to Identify and Explain Interactions among Independent Greenhouse Climate Control Requirements

The slow adoption pace of new control strategies for sustainable greenhouse climate control by industrial growers, is mainly due to the complexity of identifying and explaining potentially conflicts when integrating independently climate control requirements. In this paper, we show how the satisfiability of agents, implementing independent climate control requirements, can be used to identify and explain conflicting control interactions, which emerge because the agents share the same resources in the controlled environment. Potential conflicts due to unfulfilled climate control requirements correspond to low agent satisfiability. Low satisfiability indicates that an agent’s goal is conflicting with the proposed settings of the greenhouse climate. This allows us to explain to which degree independent climate control requirements are fulfilled by visualizing the satisfiability of the corresponding agents. We have evaluated our approach using real climate control data. The evaluation showed that it is possible to identify and explain conflicts among agents sharing the same controlled environment.

Jan Corfixen Sørensen, Bo Nørregaard Jørgensen, Yves Demazeau

A Multi-Agent System for Industrial Fault Detection and Repair

A Multi Agent System is described, capable of monitoring a telecommunication industrial test & measurement setup, designed as an application of the DALI agent language. The autonomy of the MAS is necessary to supervise the measurement apparatus during off-work time without human intervention, increasing the quality and efficacy of the overall test procedure. The MAS can decide whether to recover or repair the set of software process needed to achieve a correct test sequence without user intervention.

Vincenzo Bevar, Stefania Costantini, Arianna Tocchio, Giovanni De Gasperis

A Virtual Selling Agent Which Is Proactive and Adaptive

In this paper, we claim that the online selling process can be improved if the experience of the customer is closer to the one in a retailing store. For this purpose, we aim at providing a virtual selling agent that is proactive and adaptive. Our proactive dialogical agent initiates the dialogue, uses marketing strategies and drives the inquiring process for collecting information in order to make relevant proposals. Moreover, our virtual seller is adaptive since she is able to adjust her behaviour according to the buyer profile.

Fabien Delecroix, Maxime Morge, Jean-Christophe Routier

A BDI Model for Component and Service-Based Systems: Self-OSGi

This paper proposes the adoption of the Belief, Desire, Intention (BDI) agent model for the construction of component & service-based software systems with Self-* properties. It examines component/service and agent technologies, and shows how to build a component & service-based framework with agent-like autonomous features. This paper illustrates the design of one such framework, Self- OSGi, built on Java technology from the Open Service Gateway Initiative (OSGi). The use of the new framework is tested in a new test-bed designed to assess its ability to support Self-* software architectures.

Mauro Dragone

Replicating Hofstede’s Cultured Negotiation

Hofstede et al. cultured negotiating agents simulation produced realistic behavior by incorporating Hofstede’s dimensional model of culture in the agent’s negotiation protocol and overall behavior. Given such a promising model to generate actual human-like behavior in artificial agents, and the lack of sound and well accepted replication methodologies, we tried to remake the original simulation and highlight the roadblocks encountered during the process. Some suggestions are made in order to avoid such obstacles. New results showed a relational equivalence.

João Graça, Helder Coelho

Toward a Spatially-Centered Approach to Integrate Heterogeneous and Multi-scales Urban Component Models

This article addresses a model coupling based approach (i.e reusing and combining spatial models) for modeling and simulating complex systems. Our research is conducted by a land use program of Métouia city (Tunisia) for which administration would study (by simulations) different planning scenarios to identify strategies of industrial development. These simulations should take into account demographic, socio-economic and environmental factors. Many urban models are available but they do not integrate these three aspects. This limitation could be solved by a model coupling based approach. In this paper, from an analysis of models and approaches presented in the literature, we identify key points, needs and the basis of an approach to couple models. Then, we introduce an original approach, based on agent paradigm, in which space is the coupling factor to interconnect heterogeneous models (mathematical models, stochastic models, individual based models, and so on). The pertinence of this coupling approach is also raised by the correlation to observe the impact of models on each other.

Ines Hassoumi, Christophe Lang, Nicolas Marilleau, Moncef Temani, Khaled Ghedira, Jean Daniel Zucker

Combination of an Evolutionary Approach and Multi-agent Coalition in a Co-modal Transport System

This paper addresses the problem of optimization in a distributed co-modal transport system. Transport systems are usually geographically distributed in dynamic changing environments. Such a system has to reach various sources in order to produce the necessary co-modal information for assisting the transport users and satisfying their requests. In this context, agent based technology might be very efficient. In this paper, we propose a combination of an evolutionary method and a multi-agent coalition in order to satisfy and optimize transport user itineraries demands in terms of total cost, total travelling time and total greenhouse gas emission. The presented co-modal transport system takes into account all possible means of transport, including carpooling, free use vehicles and public transport.

Karama Jeribi, Hinda Mejri, Hayfa Zgaya, Slim Hammadi

Towards Parallel Real-Time Trajectory Planning

This paper exploits the computing power of widely available multi-core machines to accelerate the trajectory planning by parallelisation of the search algorithm. In particular we investigate the approach that schedules the workload on the cores using the hashing function based on the geographical partitioning of the search space. We use this approach to parallelize the AA* algorithm. In our solution, each partition of the geographical space is represented as an agent. The concept is evaluated on the simulation of real-time trajectory planning of aircraft respecting the environment and real aircraft performance models. We show that the approach decreases the planning time significantly on common multi-core machines preserving the quality of the trajectory provided by AA* algorithm.

Štěpán Kopřiva, David Šišlák, Michal Pěchouček

Situation Patterns in Multi-Agent Systems for Solving Transportation Problems

The aim of the work is to propose algorithms which solve transportation problems, viz. Pickup and Delivery Problem with Time Windows (PDPTW), taking into consideration the identification and description of the current situation. The essential element of a solution is to calculate measures of the current situation and use them to decide on versions and configurations of algorithms performed dealing with given kinds of problems the best and limit the computational time.

Jarosław Koźlak, Sebastian Pisarski, Małgorzata Żabińska

Traffic Behavioral Simulation in Urban and Suburban – Representation of the Drivers’ Environment

The aim of this paper is to improve the validity of traffic simulations in urban and suburban fields, with a better consideration of the driving context and driver behavior in terms of anticipation of positioning on the lanes and occupation of space. Our model is based on a multi-agent approach and the emergence concept. The simulation intends to reproduce the observed behavior such as filtering between vehicles (two-wheels, emergency vehicles), prepositioning on lanes when approaching the road intersections, “exceptional” situations (stranded vehicle or improperly parked, etc.). The proposed approach considers that each driver is perceiving the situation in an ego-centered way and is readapting the road space by overriding the existing physical structure.

Feirouz Ksontini, Stéphane Espié, Zahia Guessoum, René Mandiau

Automated Generation of Various and Consistent Populations in Multi-Agent Simulations

The variety and consistency of the agents behaviors greatly influences the realism in multi-agent simulations, and designing scenarios that simultaneously take into account both aspects is a complex task. To address this issue, we propose an approach to automatically create populations using sample data. It facilitates the designers tasks, and variety as well as consistency issues are handled by the generation model. The proposed approach is based on a behavioral differentiation model that describes the behaviors of agents using norms. To automatically configure this model, we propose an inference mechanism based on Kohonen networks and estimation distribution functions.We then introduce agents generators that can create a specified population, and are automatically configured by the inferred norms. The approach has been evaluated in traffic simulation, in association with a commercial software. Experimental results show that it allows to accurately reproduce the populations represented in sample data.

Benoit Lacroix, Philippe Mathieu

An Applied Agent-Based Model for Path-Planning on a Mobile Device

Navigation applications have a large development base in robotics, gaming, asset tracking, networking, and more. The principle of a navigation system encompasses a number of areas (e.g. localization, path-planning, map generation, etc). This project presents a multi-agent path-planning simulation and the communication protocols designed for the agents. It describes the initial agents’ functions in the proof-of-concept of our application. The model was implemented on a mobile device in order to simulate a navigation system adapted to indoor environments. The goal of the project was a proof-of-concept of an agent-based model.

Teresa A. Shanklin, Benjamin Loulier, Eric T. Matson, J. Eric Dietz

Virtual Customers in an Agent World

The relevance of multi-agent systems (MAS) has been demonstrated in computer simulations or video games where many autonomous entities interact in a complex and dynamic environment. Serious Games (SG) are a new discipline situated at the edge of computer simulation and games. We advocate that a certain category of SG, where the player is immersed in a 3d environment, represents a particularly interesting testbed for MAS, for they introduce novel and inspirational problematics for the community. In this paper, we explore the challenges posed by these immersive SG to the MAS approach. Particularly, we demonstrate that the IODA interaction-oriented MAS approach, answers these new problematics with efficacy. We illustrate our discussion with a SG project developed in our team.

Philippe Mathieu, David Panzoli, Sébastien Picault

Non-invasive Estimation of Stress in Conflict Resolution Environments

The current trend in Online Dispute Resolution focuses mostly on the development of technological tools that allow parties to solve conflicts through telecommunication means. However, this tendency leaves aside key issues, namely our concern with respect to context information that was previously available in traditional Alternative Dispute Resolution processes. The main weakness of this approach is that conflict resolution may become a cold process, focused solely on objective questions. In order to overcome this inconvenience, we move forward to incorporate context information in an Online Dispute Resolution platform. In particular, we consider the estimation of the level of stress of the users by analyzing their interaction patterns. As a result, the conflict resolution platform or the mediator may weight to what extent a party is affected by a particular matter, allowing one to adapt the conflict resolution strategy to a specific problem in real time.

Paulo Novais, Davide Carneiro, Marco Gomes, José Neves

A JaCaMo-Based Governance of Machine-to-Machine Systems

Machine-to-Machine (M2M)

systems compose smart networks of multiple devices sensing or acting in the physical world, and interacting together to provide data to value-added services. M2M infrastructures aiming at being deployed city wide have to deal with the increasing number of services and applications they have to support. A dynamic sharing of M2M infrastructure between applications is thus a strong requirement. In this paper, we propose to use multi-agent abstractions and related programming languages to define an adaptive and agile layer to govern M2M infrastructure to support different applications.

Camille Persson, Gauthier Picard, Fano Ramparany, Olivier Boissier

Evaluation of a Multi-Agent System for the Evolving of Domain Ontologies from Texts

Ontologies are one of the most used representation to model the domain knowledge. An ontology consists of a set of concepts connected by semantic relations. Manual ontology building and evolving are difficult and complex tasks. This paper presents DYNAMO, a software based on a Multi-Agent System (MAS) that automates these tasks. Terms and concepts of a given domain are agentified. These agents cooperate to determine their place in the MAS (that is the ontology) thanks to (

i

) lexical relations between terms, (

ii

) some adaptive mechanisms enabling addition, removing or moving of new terms, concepts and relations in the ontology as well as (

iii

) feedbacks from the ontologist about the propositions given by the MAS. This paper presents the architecture of DYNAMO, its mechanisms for ontology evolution and its evaluations.

Zied Sellami, Valérie Camps

Multitarget Flocking for Constrained Environments

Flocking algorithms allow high level organization in huge groups of agents. We deal with a multitarget variation of flocking. In this variation, each agent chooses a target to follow, and several flocks are formed then. One important disadvantage of the previously proposed multitarget flocking models is that they assume that agents move in an environment without restrictions. That is, there are no objects that constrain the mobility of agents, such as obstacles. This drawback limits potential applications of multitarget flocking models such as multirobot systems and unmanned aerial vehicles. In this work, we proposed a stable multitarget algorithm based on Particle Swarm Optimization to solve the problem mentioned above. System behavior was rigorously measured to conclude that our proposal models multitarget flocking in constrained environments.

Armando Serrato Barrera, A. López-López, Gustavo Rodríguez Gómez

Emotional Decision Making in Large Crowds

Currently it is widely recognised that emotions of people influence their decisions. In this paper the role of emotions in social decision making in large technically assisted crowds is investigated. For this a formal, computational model is proposed, which integrates existing neurological and cognitive theories of affective decision making. Based on this model several variants of a large scale crowd evacuation scenario with technically assisted agents were simulated. By analysis of the simulation results it was established that spread of emotions in a crowd increases resistance of agent groups to opinion changes and supports continuity of decision making in a group with technically assisted agents.

Alexei Sharpanskykh, Kashif Zia

Game Theoretical Adaptation Model for Intrusion Detection System

We present a self-adaptation mechanism for Network Intrusion Detection System which uses a game-theoretical mechanism to increase system robustness against targeted attacks on IDS adaptation. We model the adaptation process as a strategy selection in sequence of single stage, two player games. The key innovation of our approach is a secure runtime game definition and numerical solution and real-time use of game solutions for dynamic system reconfiguration. Our approach is suited for realistic environments where we typically lack any ground truth information regarding traffic legitimacy/maliciousness and where the significant portion of system inputs may be shaped by the attacker in order to render the system ineffective. Therefore, we rely on the concept of challenge insertion: we inject a small sample of simulated attacks into the unknown traffic and use the system response to these attacks to define the game structure and utility functions. This approach is also advantageous from the security perspective, as the manipulation of the adaptive process by the attacker is far more difficult. Our experimental results suggest that the use of game-theoretical mechanism comes with little or no penalty when compared to traditional self-adaptation methods.

Jan Stiborek, Martin Grill, Martin Rehak, Karel Bartos, Jan Jusko

Distributed Optimization of Finite Resource Planning for Asincronous and Non-linear Systems: Application to Power Management

This paper introduces a Multiagent System (MAS) for optimal resource planning in non-linear systems. The distributed planning strategy, which is based on interaction of agents, is composed by two phases. The first one uses an iterative double auction based protocol and allows requesting for getting back the previously allocated resources in order to establish a better planning. The second phase takes the previous resource allocation for finding better alternative paths. The proposal has been applied into our house-lab power system for optimize the use of renewable power supplies. Power production and requirements are simulated using the average of power consumption measures of each component.

Rafael J. Valdivieso-Sarabia, Francisco J. Ferrandez-Pastor, Juan M. Garcia-Chamizo

An Agent Based Trust Management System for Multi-Agent Based Virtual Communities

The success of a virtual community relies on collaboration and resource sharing principals, making trust a priority for each member. Such systems need a flexible trust model wherein trust policies are automatically adapted and where both individual and collective trust requirements are considered in the decision making-process. This paper reports our on-going efforts in that direction. It presents an agent based Adaptive and Socially-Compliant Trust Management System (ASC-TMS) for multi-agent based virtual communities.

Reda Yaich, Olivier Boissier, Gauthier Picard, Philippe Jaillon

An Agent-Based Augmented Reality Demonstrator in the Domestic Energy Domain

In this work we propose an approach for comfortable and accelerated development of user interfaces for software agents.We apply model-based techniques and emphasise the capability of this technique by describing two user interfaces which are different in nature, but have been developed with the same model. We present the applicability of both user interfaces by means of an agent-based application in the domestic energy domain. As opposed to similar approaches we retain all degrees of freedom for the applied multi-agent framework.

Sebastian Ahrndt, Johannes Fähndrich, Marco Lützenberger, Andreas Rieger, Sahin Albayrak

Weight Optimization of Aircraft Harnesses

Nowadays aircrafts require more electrical systems. Functions usually carried out by mechanical, hydraulics or pneumatics systems are now carried out by electrical systems. Thus there is a densification of electrical systems. An aircraft electrical system is made of several electrical harnesses which are assemblies of cables and connective devices. A cable may contain one or several wires in a common covering. Thus wiring may be seen as a system of systems. In parallel, a link connects (functionally) equipments through harnesses.

Stéphanie Combettes, Thomas Sontheimer, Sylvain Rougemaille, Pierre Glize

A Virtual Selling Agent Which Is Proactive and Adaptive: Demonstration

In this demonstration, we bring the online selling process closer to the customer experience in a retailing store. For this purpose, we demonstrate a virtual selling agent that is proactive and adaptive. Our proactive dialogical agent initiates the dialogue and drives the inquiring process for collecting information in order to make relevant proposals. Moreover, we will see that our virtual seller is adaptive since she is able to adjust her behaviour according to the buyer profile.

Fabien Delecroix, Maxime Morge, Jean-Christophe Routier

Demonstrator of a Multi-Agent System for Industrial Fault Detection and Repair

A demonstrator of a Multi Agent System is described capable of monitoring a telecommunication industrial test & measurement setup, designed as an application of the DALI agent language. The autonomy of the MAS is necessary to supervise the measurement apparatus during off-work time without human intervention, increasing the quality and efficacy of the overall test procedure. The MAS can decide whether to recover or repair the set of software process needed to achieve a correct test sequence without user intervention.

Giovanni De Gasperis, Vincenzo Bevar, Stefania Costantini, Arianna Tocchio, Alessio Paolucci

Demo: A BDI Model for Component and Service-Based Systems: Self-OSGi

This paper illustrates the use of Self-OSGi - a novel agent toolkit built on the Open Service Gateway initiative (OSGi) to ease the construction of adaptive component & service-based software systems.

Component & service orientation is a highly popular approach for building adaptive software solutions, for instance, as part of Robotic and Smart Environment applications. Component frameworks operate by posing clear boundaries (in terms of provided & required service interfaces) between components and by guiding the developers in re-using and assembling these components into applications.

Mauro Dragone

Group Coordination for Agent-Oriented Urban Traffic Management

Future cooperative traffic management systems will make use of on-board intelligence and of communication among vehicles and traffic infrastructure. In this demonstration, we present a simulation-based approach of applying multi-agent systems modeling and coordination for dynamic traffic management in urban areas. Traffic participants, modeled as agents, act according to their local goals and preferences under the more global constraints of traffic management. Towards this end, our approach employs decentral coordination and cooperation techniques. We demonstrate (i) a group coordination mechanism allowing groups of vehicles to select their common speed based on a chosen route; and (ii) a group-oriented automated driving method enabling vehicle agents to co-ordinate their speed and lane choices. The demonstration uses the AIMSUN traffic simulation system which has been enhanced to support agent-based simulation.

Jana Görmer, Jörg P. Müller

A Driver Ego-Centered Environment Representation in Traffic Behavioral Simulation

We present a multi-agent traffic simulation to improve the validity of traffic simulations in urban and suburban fields, with a better consideration of the driving context and driver behavior in terms of anticipation of positioning on the lanes and occupation of space. The demonstration intends to reproduce the observed behavior such as filtering between vehicles (two-wheels), prepositioning on lanes when approaching the road intersections, “exceptional” situations (stranded vehicle or improperly parked, etc.). The proposed approach considers that each driver is perceiving the situation in an ego-centered way and is readapting the road space by overriding the existing physical structure.

Feirouz Ksontini, Stéphane Espié, Zahia Guessoum, René Mandiau

ROSACE: Agent-Based Systems for Dynamic Task Allocation in Crisis Management

This demonstration illustrates the AMAS self-adaptive cooperative approach to manage task allocation for robot teams in the ROSACE’s forest fire-fighting scenario. Experimental validation is based on two prototypes sharing a common simulated environment, but different robot architecture and processing.

Jérôme Lacouture, José Manuel Gascueña, Marie-Pierre Gleizes, Pierre Glize, Francisco J. Garijo, Antonio Fernández-Caballero

ANTE: Agreement Negotiation in Normative and Trust-Enabled Environments

Research on negotiation and task allocation has been in the multi-agent systems realm since its inception as a research field. More recently, social aspects of agent-hood have received increasing attention, namely developing on the fields of normative and trust systems. The integration of these different research contributions will allow to build robust applications for electronic agreement negotiation, aiming at their acceptability and application in industry.

Henrique Lopes Cardoso, Joana Urbano, Pedro Brandão, Ana Paula Rocha, Eugénio Oliveira

Graphical Configuration of Agent-Based Warehouse Management and Control Systems

Although agent technology fits naturally to the control of the massively parallel processes in warehouses, agent-based warehouse management and control systems (WMCSs) have hardly been used in industry. We argue that model-driven development of such systems is crucial for their industrial applicability.We present a graphical configuration tool that provides a user-friendly means to specify agent-based WMCSs. With this tool, warehouse system architects can specify a WMCS without detailed knowledge of the underlying implementation and without a large programming effort: a WMCS is generated from the architect’s specification.

Hsuan Lorraine Liang, Jacques Verriet, Roelof Hamberg, Bruno van Wijngaarden

Introducing ATOM

Elements of Context

In recent years, Artificial Intelligence systems have received an increasing amount of academic interest in Economics and Finance. Among these works, Artificial Stock Markets (ASM) have particularly benefited from the agent based approach and from the Multi-Agent philosophy.

The application fields for Agents-based modelling and simulations in Finance appears extremely promising. For example, one can study the impact of a Tobins tax on the financial system, or one can develop new stress tests for assessing financial resilience to economic shocks or to develop new automatic trading techniques. Implementing realistic simulations of complex financial dynamics using both artificial intelligence, distributed agents and realistic market algorithms gives the researcher a powerful tool for understanding stylized facts and for experimenting various regulations in a controlled, riskless experimental environment.

Philippe Mathieu, Olivier Brandouy

An Immersion into a Multi-agent Store Simulation

FORMAT-STORE is a Serious Game (SG) in 3d designed in collaboration with the game studio Idées-3Com and the business school ENACO, aimed at training undergraduate students to the management of a convenience store and customer relationship. In FORMAT-STORE, the learner is immersed in a virtual replica of a store populated by artificial customers, so as to practice daily activities of a salesperson. Immersive SG raise specific issues as explained in [3]. An Interaction-Oriented approach such as IODA [2] offers a particularly convenient way to address the multiple problems of such a SG simultaneously.

Philippe Mathieu, David Panzoli, Sébastien Picault

Incorporating Stress Estimation into User-Centred Agent-Based Platforms

Current virtual environments for communication, cooperation and problem solving lack the rich context information that is present in face-to-face interactions. People rely on this context information, that includes body language or level of stress just to name a few, to take decisions. In this paper we present an approach whose objective is to be able to acquire context information about the users of such technological tools, making that information available for the tool and eventually to other people. We present a prototype being developed in the context of an agent-based conflict resolution platform. As a result, we achieve communication and problem solving virtual environments that are richer and closer to traditional environments, allowing people and software agents to take better and more rational decisions.

Paulo Novais, Davide Carneiro, José Neves

DYNAMO-MAS: A Multi-Agent System for Building and Evolving Ontologies from Texts

Building and evolving an ontology are a complex problems: they involve numerous entities (terms, concepts, relations), the environment of the ontology is dynamic (addition of new documents, ontologist’s actions) and we cannot predict all ontology evolution possibilities. That is why a unique entity or system to solve these problems cannot list all the possible situations to which it can be confronted as well as the actions it has to take in such situations. This compels to distribute the problem on several autonomous entities that have a local perception of each situation that can arise during the system functioning and that have simple, generic and local behaviors in order to self-adapt to these situations. We propose in that sense DYNAMO-MAS, a tool based on a Multi-Agent System (MAS) enabling the co-construction and the evolving of an ontology. It takes as input a corpus of texts and provides as output an ontology.

Zied Sellami, Valérie Camps

Demonstration of Multitarget Flocking for Constrained Environments

Flocking models allow high level organization in huge groups of agents. We deal with a multitarget extension of flocking. In this extension, each agent chooses a target to follow, and several flocks are formed then. In comparison with previous multitarget flocking algorithms, our proposal can handle several obstacles in the environment and it is based on the Particle Swarm Optimization Algorithm. Simulations have shown that the desired behavior of the system was achieved. Our future work considers the extension of the model for 3D environments.

Armando Serrato Barrera, A. López-López, Gustavo Rodríguez Gómez

Game Theoretical Adaptation Model for Intrusion Detection System - Demo Paper

We present a self-adaptation mechanism for Network Intrusion Detection System which uses a game-theoretical mechanism to increase system robustness against targeted attacks on IDS adaptation. This system has been used to ensure the robustness of commercially provided software used by clients throughout the world. It is particularly important to prevent the long-term persistence of advanced attackers operating in the compromised networks by relying on the game-theoretical mechanism to ensure the long-term diversity of the detection boundary.

Jan Stiborek, Martin Grill, Martin Rehak, Karel Bartos, Jan Jusko

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