Ioanna Stamatopoulou

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.

Modelling dynamic organization of biology-inspired multi-agent systems with communicating x-machines and population p systems

Dynamic organization of multi-agent systems can be inspired by the way biological systems adapt to the evolution of their components. In this paper, we investigate how multi-agent systems can be formally modelled as well as how their configurations can be altered, thus affecting the communication between agents. We use two different formal methods, communicating X-machines and population P systems with active membranes, in order to model the case of flocking agents. Each method possesses different appealing characteristics which are examined through the modelling process.

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.

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.

OPERAS: A Framework for the Formal Modelling of Multi-Agent Systems and Its Application to Swarm-Based Systems

Swarm-based systems are a class of multi-agent systems (MAS) of particular interest because they exhibit emergent behaviour through self-organisation. They are biology-inspired but find themselves applicable to a wide range of domains, with some of them characterised as mission critical. It is therefore implied that the use of a formal framework and methods would facilitate modelling of a MAS in such a way that the final product is fully tested and safety properties are verified. One way to achieve this is by defining a new formalism to specify MAS, something which could precisely fit the purpose but requires significant period to formally prove the validation power of the method. The alternative is to use existing formal methods thus exploiting their legacy. In this paper, we follow the latter approach. We present OPERAS, an open framework that facilitates formal modelling of MAS through employing existing formal methods. We describe how a particular instance of this framework, namely OPERAS XC , could integrate the most prominent characteristics of finite state machines and biological computation systems, such as X-machines and P Systems respectively. We demonstrate how the resulting method can be used to formally model a swarm system and discuss the flexibility and advantages of this approach.

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.

OPERASCC: an instance of a formal framework for MAS modeling based on population P systems

Swarm-based systems are biology-inspired systems which can be directly mapped to multi-agent systems (MAS), possessing characteristics such as local control over the decisions taken by the agents and a highly dynamic structure which continuously changes. This class of MAS is of a particular interest because it exhibits emergent behavior through self-organization and finds itself applicable to a wide range of domains. In this paper, we present OPERAS, an open formal framework that facilitates modeling of MAS, we describe how a particular instance of this framework, namely OPERASCC, could employ existing biological computation systems, such as population P systems, and demonstrate how the resulting method can be used to formally model a swarm-based system of autonomous spacecrafts.

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.

Formal modelling of agents acting under artificial emotions

Artificial Agents infused with emotions have attracted considerable attention in recent years. Many domain areas require agents to be able to demonstrate an emotional reaction to stimuli, beliefs, goals, communication etc., thus exhibiting a believable behaviour. On the other hand, little has been said on how formal methods could integrate emotions in a form of rigorous mathematical notation. This paper is an initial attempt to infuse a formal modelling method for reactive agents, namely X-machines, with appropriate attributes that model artificial emotions. X-machines are finite state-based models extended with memory as well as functions that are applied on input and memory values. X-machines have been shown to be particularly useful to model reactive agents. The computation, that is the overall behaviour of an agents, is a sequence of states reached through the application of transition functions (actions that an agent performs). This computation is amended when artificial emotions are involved, thus leading to a different overall behaviour when an agent acts under artificial emotions. After discussing basic theories on emotions and their role to creating believable agents, we present the definition of the eX-machine (eχ) and its computation. A simple multi-agent system with emotional reactive agents is used to show the formal modelling process. Additionally, the same example is used to demonstrate how a visual simulation, based on eχ formal modelling, has different behaviour of the overall system, when artificial emotions are applied.