Abstract
Simulation is often used to forecast human populations. In this paper we use a novel approach by combining Micro-Macro (MicMac) models into an Agent-Based perspective to simulate and forecast the behavior of the Portuguese population. The models include migrations and three scenarios corresponding to three different expected economic growth rates. We conclude that the increase in the number of emigrants leads to a reduction of the Portuguese women that are in the fertile age. This justifies the decrease of births and therefore the general decrease of the total Portuguese Population.

Abstract
Simulation is a computer-based experimentation tool suitable to determine the efficacy of a previously untried decision. In this paper, we present a model of climate change. The goal behind this project is to provide a test-bed to evaluate theories related to the Earth system so as to test and evaluate metrics such as greenhouse gases and climate change in general. The proposed approach is based on a multi-agent model which has as input a representation of nature and as output the changes that will occur on Earth within a given instant of time. Most views about climate change do not take into account the real severity of the subject matter; however, the present perspective is given in a way so as to make non-experts aware of the risks that are threatening life on Earth. Just recently, the general population has developed considerable sensitivity to these issues. One important contribution of this work is to use agent-based modeling and simulation as an instructional tool that will allow people to easily understand all aspects involved in the preservation of the environment in a more aware and responsible way.

Abstract
In order to improve their competitive performance, airline companies often adopt as a strategy to establish arrangement between two or more organizations agreeing to cooperate on a substantial level. This strategy is often known as airline alliances. A paradigm to analyze the collective intelligence behavior which emerges from a group, as a strategic alliance, is the flocking behavior. Inspired by the Cucker and Smale algorithm (C-S) we propose a new version of the flocking behavior algorithm applied to airline alliances. Our goal is to understand the link between strategic alliances and flocks. For this new approach, metrics were obtained for the parameters of C-S algorithm, namely position, velocity and influence, where the latter uses cooperative games. Besides, reinforcement learning mechanisms have been explored. Some relevant outputs for airline alliances as the permanence rate and the growth rate were computed for each of the five configurations in analysis.

Abstract
In traffic & transportation system analysis the way individuals make choices plays a paramount role as these will affect the general efficiency with which people can travel. Modifications on the system by means of policy intervention affect commuters' perspective impacting on the performance of the network and eventually on the society's welfare. The emergence of system's behaviour, as a result of decisions at individual level, provides the traffic manager with the opportunity to evaluate modifications that have been implemented on the system. However, there has been a slow advance in appropriately representing users and their behaviour in all social dimensions of intelligent transportation systems. This paper discusses on a social-oriented modelling & simulation framework for Artificial Transportation Systems, which accounts for different social dimensions of the system in the assessment and application of policy procedures. We illustrate how a social agent-based model can be a useful tool to test the appropriateness and efficiency of transportation policies.

Abstract
This study reviews performance criteria adequate to validate simulation models through the comparison of two quantitative data sets, concerning historical and simulated data. The criteria reviewed were organized according to its characteristics into the groups: error-based measures, information theory measures, information criteria, parametric tests, non-parametric tests, distance-based measures and combined measures. Each criterion is reviewed through its mathematic definition, its applications in literature and the identification of its advantages and drawbacks. The features assessed by each criterion are identified and discussed. This study provides a concise outline over the criteria reviewed, which can be used as a guide to help developers of simulation models into the decision on the most appropriate criteria to validate their models.

Abstract
In this paper, we present a computing procedure to analyze a network of credit and debt among agents (nodes) from a standpoint of balance sheet dependencies. The aim is to develop a method to assess thoroughly the sensitivity of the network to potential individual insolvencies. For this purpose, given a state of the network, the insolvency of an agent is assumed and the cascade of provoked insolvencies is simulated. Exploring the matrix definition of the network, this is made systematically for all agents. Therefore, in only one run of the procedure, all the possible trajectories of insolvencies, each beginning in a different agent, are calculated. This allows spotting at a glance which agents are "systemically riskier". Determination of adequate capital levels can be made on a case basis by running the procedure repeatedly. This work contributes with two new aspects to the existing literature. First, given a known situation of a credit and debt network, a computing procedure is presented that allows to assess the network sensitivity to the exogenous insolvency of any of its nodes. Second, continued monitoring of a credit and debt network is computationally feasible. This "proof of concept" software can be extended into a tool useful for research and regulation, if the relevant information is made available.