4 research outputs found

    A crystal ball made of agents

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    This article presents an agent-based solution to model the opinions of an experts group with the aim of predicting possible future scenarios. The need to envision the future is not new; it has existed since the beginning of human-kind. What it is new is the applicable technology that is available in a specific period of time. It is not usual to find a critical social system which evolves according to predictable guidelines or tendencies. Because of that reason, technical prediction based on past and present data is not reliable. This paper includes the process description of eliciting information from a group of experts and a real case study

    Prospecting the future with AI

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    If we were able to foresee the future, we could be prepared to reduce the impact of bad situations as well as getting the most of profiting periods. Our world is a dynamic system that evolves as time goes by. The number of variables that can influence in future situations outnumbers our capacity of prediction at a first glance. This article will show an alternative way to foresee potential future scenarios based on human experts’ opinion, what can be considered as a knowledge modeling tool

    An Agent-Based Approach for Data Fusion in Homeland Security

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    This article presents an agent-based solution for data fusion in Homeland Security. Communication technology has been developed very fast in the last decades. We can get lots of data in milliseconds. Our current problem is to process such amounts of data in order to provide useful information. We have to focus our effort on developing intelligent information systems able to handle big amounts of data extracting or revealing relations among data and able to produce information easily understandable for the human user. That is the case of data fusion in tactical operations, especially in the field of defense and Homeland security. Our research is focused on obtaining a Multi-agent system able to inference future enemy’s actions or behaviors from data received from heterogeneous sensors
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