Abstract
In recent years various methods from the field of artificial intelligence (AI) have been applied to economic problems. The subarea of multiagent systems (MAS) is particularly useful as it enables to simulate individuals or organizations and various interactions among them. In this paper we investigate a scenario with a set of agents, each belonging to a certain sector of activity (e.g. agriculture, clothing, health sector etc.). The agents produce, consume goods or services in their area of activity. Besides, our model includes also the resource of free time. The goods and resources are exchanged on a market governed by auction, which determines the prices of all goods. We discuss the problem of developing an adaptive producer that exploits reward-based learning. This facet enables the agent to exploit previous information gathered and adapt its production to the current conditions. We describe a set of experiments that show how such information can be gathered and explored in decision making. Besides, we describe a scheme that we plan to adopt in a full-fledged experiments in near future.

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This work explores an application of the spatial prisoner's dilemma in two situations: when all agents use the same type of behavior and when they use a mix of behaviors. Our aim is to explore the evolutionary dynamics of this game to analyze the dominance of one strategy over the other. We also investigate, in some possible scenarios, which behavior has better performance when they all coexist in the same environment.

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In this study, we analyze firms' membership in R&D (Research and Development) cooperation networks trough simulation methods. Our main research hypothesis is that the membership in cooperation networks is related to the degree of the knowledge spillover. The approach has two scenarios: cost symmetry and cost asymmetry. We first develop an analytical model with three stages: firstly, firms decide whether to participate in a cooperative research network; secondly they simultaneously choose the level of R&D output, and finally they choose the level of output. Then we proceed with computational simulations to verify our hypothesis. From our results, we were able to conclude that cooperation leads to an improvement on RJV firms' position in the market as they produce more than others with the same production conditions. Additionally, cooperating firms have to spend fewer resources on research, which turns the network a tremendous success on the productive efficiency level.

Abstract
Reaching the United Nations Millennium Development Goals and the necessary statistical literacy for citizens' understanding of what they entail requires that National Statistical Offices (NSOs) become more involved in the promotion of statistical literacy in cooperation with national statistical societies, international organizations like IASE and ISLP and national education institutions. All these stakeholders share an interest in the promotion of statistical literacy in schools yet for rather different reasons. Sharing the different skills that each possesses could have benefits for the long term goals of each stakeholder, could help improve school curricula, contribute to the debate on what constitutes statistical literacy and what is the best way to help citizens achieve it, and make the path to evidence based decision making easier. In this paper we present examples of what National Statistics Offices can and can not do regarding the promotion of statistical literacy in schools. We illustrate the common and singular aspects of their programs for schools and discuss how they follow the current trends in statistics education while helping the National Statistics Office's goal of promoting their statistics products and creating more users of official statistics. The work of the International Statistical Literacy Project (ISLP) is discussed in the context of drawing together stakeholders and resources.