Ilias Sakellariou

Enhancing NetLogo to Simulate BDI Communicating Agents

The implementation process of complex agent and multi-agent systems (AMAS) can benefit significantly from a simulation platform that would allow rapid prototyping and testing of initial design ideas and choices. Such a platform, should ideally have a small learning curve, easy implementation and visualisation of the AMAS under development, while preserving agent oriented programming characteristics that would allow to easily port the design choices to a fully-fledged agent development environment. However, these requirements make such a simulation platform an ideal learning tool as well. We argue that NetLogo meets most of the requirements that suit our criteria. In addition, we describe two extra NetLogo libraries, one for BDI-like agents and one for ACL-like communication that allow effortless development of goal-oriented agents, that communicate using FIPA-ACL messages. We present one simulation scenario that employs these libraries to provide an implementation in which agents cooperate under a Contract Net protocol.

ExperNet: an intelligent multiagent system for WAN management

The authors describe ExperNet, an intelligent multiagent system developed to assist in managing large-scale data networks. The system assists network operators at various nodes of a WAN to detect and diagnose hardware failures and network traffic problems, suggesting the most feasible solution through a Web-based interface.

Transforming communicating X-machines into P systems

Tissue P systems (tPS) represent a class of P systems in which cells are arranged in a graph rather than a hierarchical structure. On the other hand, communicating X-machines (XMs) are state-based machines, extended with a memory structure and transition functions instead of simple inputs, which communicate via message passing. One could use communicating XMs to create models built out of components in a rather intuitive way. There are investigations showing how various classes of P systems can be modelled as communicating XMs. In this paper, we define a set of principles to transform communicating XMs into tPS. We describe the rules that govern such transformations, present an example to demonstrate the feasibility of this approach and discuss ways to extend it to more general models, such as population P systems, which involve dynamic structures.

System architecture of a distributed expert system for the management of a national data network

The management of large data networks, like a national WAN, is without any doubt a complex task. Taking into account the constantly increasing size and complexity of todays TCP/IP based networks, it becomes obvious that there is a demanding need for better than simple monitoring management tools. Expert system technology seems to be a very promising approach for the development of such tools. This paper describes the system architecture of ExperNet, a distributed expert system for the management of the National Computer Network of Ukraine, and the implementation of the tools used for its development. ExperNet is a multiagent system built in DEVICE, an active OODB enhanced with high level rules, that uses CS-Prolog II to implement the communication facilities required. The system employs HNMS+ and Big-Brother, two modified versions of existing network management tools, in order to obtain a complete view of the monitored network.

Evacuation Simulation through Formal Emotional Agent based Modelling

Evacuation Simulation is recognised as an important tool for assessing design choices for urban areas. Although a number of approaches have been introduced, it is widely acceptable that such simulation scenarios demand modelling of emotional aspects of evacuees, and how these affect their behaviour. The present work, proposes that formal agent modelling based on eX-machines can rigorously define but also naturally lead to realistic simulations of such scenarios. eX-machines can model agent behaviour influenced by emotions, including social aspects of emotions, such as emotion contagion. The developed formal model is refined to simulation code, that is able to visualise and simulate crowd believable behaviour.

myVisitPlanner GR : Personalized Itinerary Planning System for Tourism.

This application paper presents myVisitPlanner GR, an intelligent web-based system aiming at making recommendations that help visitors and residents of the region of Northern Greece to plan their leisure, cultural and other activities during their stay in this area. The system encompasses a rich ontology of activities, categorized across dimensions such as activity type, historical era, user profile and age group. Each activity is characterized by attributes describing its location, cost, availability and duration range. The system makes activity recommendations based on user-selected criteria, such as visit duration and timing, geographical areas of interest and visit profiling. The user edits the proposed list and the system creates a plan, taking into account temporal and geographical constraints imposed by the selected activities, as well as by other events in the user’s calendar. The user may edit the proposed plan or request alternative plans. A recommendation engine employs non-intrusive machine learning techniques to dynamically infer and update the user’s profile, concerning his preferences for both activities and resulting plans, while taking privacy concerns into account. The system is coupled with a module to semi-automatically feed its database with new activities in the area.

Experiments with Emotion Contagion in Emergency Evacuation Simulation

Multi-agent systems simulation is used to predict human behaviour in emergency evacuation cases. However, as human behaviour can change under the effect of emotions, it is essential to create models of artificial agents and simulations that mimic such behaviour in order to make prediction of the overall system performance. In emotional agents, the role of emotional contagion is important. Emotional contagion is a result of interaction between agents which could affect each others emotions. It is the case that in emergency situations, emotions (especially calmness, fear and panic) may propagate in various ways, depending on the agents personality type as well as other factors. In this paper, we review various methods of emotional contagion. In order to develop emotional agent simulation, we start from a formal state-based modelling method and devise a number of variations of known emotional contagion methods. NetLogo visual simulation is used, in which a number of experiments is conducted. The results are useful to demonstrate different behaviour of different emotional contagion models in the evacuation of an open square area.

A Formal Approach to Model Emotional Agents Behaviour in Disaster Management Situations

Emotions in Agent and Multi-Agent Systems change their behaviour to a more ’natural’ way of performing tasks thus increasing believability. This has various implications on the overall performance of a system. In particular in situations where emotions play an important role, such as disaster management, it is a challenge to infuse artificial emotions into agents, especially when a plethora of emotion theories are yet to be fully accepted. In this work, we develop a formal model for agents demonstrating emotional behaviour in emergency evacuation. We use state-based formal methods to define agent behaviour in two layers; one that deals with non-emotional and one dealing with emotional behaviour. The emotional level takes into account emotions structures, personality traits and emotion contagion models. A complete formal definition of the evacuee agent is given followed by a short discussion on visual simulation and results to demonstrate the refinement of the formal model into code.

Formal Agent-Based Modelling and Simulation of Crowd Behaviour in Emergency Evacuation Plans

Crowd behaviour deviates from normal when an emergency evacuation is needed. Thus, simulation of evacuation situations has been identified as an important tool for assessing design choices of urban areas, such as buildings, stadiums, etc., and Agent Based Modelling has been employed to tackle such problems. In this paper, we propose that formal modelling can rigorously define but also naturally lead to realistic simulations of such cases. Our main contribution is presenting how formal state based methods, namely X-machines, can be employed to model agents in emergency evacuation plans. We also discuss the role of emotions, model artificial emotions that change the behaviour of agents under emergency situations, and provide a formalism that models the role of emotions and personality traits in order to create a more realistic scenario. Finally, we demonstrate how the developed formal models can be refined to code, a combination of Net logo and Prolog in this case, that is able to simulate crowd behaviour with and without artificial emotions.

CSPCONS: A Communicating Sequential Prolog with Constraints

CSPCONS is a programming language that supports program execution over multiple Prolog processes with constraints. The language is an extended version of Csp-ii, a version of Prolog that supports, among other features, channel-based communicating processes and TCP/IP communication and is based on the CSP model introduced by Hoare. CSPCONS inherits all the advanced features of Csp-ii and extends it by introducing constraint solving capabilities to the processes. In CSPCONS each Prolog process has one or more solvers attached and each solver is independent from the others, following the original Csp-ii model, thus resulting to a communicating sequential constraint logic programming system. Such a model can facilitate greatly the implementation of distributed CLP applications. Currently CSPCONS offers a finite domain constraint solver, but the addition of new solvers is supported as they can be integrated in the system in the form of linkable C libraries. This paper briefly describes the original CSP-II system along with the extensions that resulted to the CSPCONS system.