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When multiple autonomous and intelligent systems are interacting together, the need of modeling each other arises. This thesis will address the problem of modeling other agents in some contexts: when these other agents are humans and when they are robots. 

The first domain is about modelling online users according to their behavior. A key challenge for companies is understanding the specific needs of their customers and adapt their services accordingly. Analyzing the behavior of customers can lead the company to provide a user-based experience, and to have useful insights on the usage of their products.
During my PhD, I plan to explore the mentioned topic: starting from raw behavioral data, I aim to build a pipeline that allows the identification of user profile types and their interpretation. The main steps of the process include data preparation, feature extraction, clustering analysis, and model interpretation.  

The second domain involves multirobot systems. Over the last decade, multirobot systems are being increasingly employed in different areas: applications can be found both in the industrial setting, such as warehouse logistics and manufacturing, and in hostile and dangerous environments, such as space, military, and rescue operations. In many realistic scenarios the environment is dynamic, meaning that unforeseen changes can happen due to factors external to our considered system, causing uncertainty.
My research addresses this challenge: the aim is to develop a method in which teams of agents are able to operate in dynamic environments in which other robot teams could appear and to adapt their behavior accordingly. The principal steps to be performed are: ;

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• a modelling phase, where agents understand if and how the environment is changing (e.g., identifying the presence and the behavior of another robot team, which could possibly represent a threat);
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• a decision and planning phase, in which agents decide the best action based on what they have processed during the previous step and adjust their plans accordingly.
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