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.
Targeted drug delivery with the use of nanorobots, a yet mostly theoretical but very promising future concept, is anticipated to become a significant ally in cancer treatment. The way that nanorobot systems are currently envisaged by researchers is such that they exhibit autonomous and collaborative behaviour that can be uniquely captured by multi-agent systems. In this paper, we investigate this hypothesis by describing the process of formally modelling a simple agent-based system for a simulation of targeted drug delivery. We propose a system comprising different types of nanorobots, and evaluate the effects of various parameters on the final outcome. The data that were retrieved from the corresponding simulation runs, are in support of our hypothesis, demonstrating that nanorobotic drug delivery systems can be effectively simulated by utilising intelligent agent technology.
This work presents an approach to agent-based simulation development using formal modelling, i.e. stream X-Machines, that combines the power of executable specifications and test case generation. In that respect, a domain specific language is presented for effortlessly encoding agent behaviour as a stream X-Machine in a well known simulation platform. The main benefits in using the specific formal approach in such a practical setting, apart from the fact that it offers a clear, intuitive way for specifying agent behaviour, is the existence of tools for test case generation, that allow to systematically generate "agent simulation test scenarios", i.e. sequences of agent inputs that can be used for validation.
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