Abstract. The implementation process of complex agent and multiagent 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 ACLlike 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.

Cloud network slicing can be defined as the process that enables isolated end-to-end and on-demand networking abstractions, which: (a) contain both cloud and network resources, and (b) are independently controlled, managed and orchestrated. This paper contributes to the vision of the NECOS project and relevant platform, that aim to address the limitations of current cloud computing infrastructures to accomplish the challenging requirements of the slicing approach. The NECOS platform implements the Slice-as-a-Service model, enabling the dynamic creation of end-to-end (E2E) slices from a set of constituent slice parts contributed from multiple domains. A challenging issue is to define the facility that implements dynamic slice resource discovery, aligned to the requirements of the slice owner or tenant, over different infrastructure providers. Here, we propose a Marketplace-based approach implementing relevant federated interactions for the resource discovery and we detail its

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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.

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