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, study, design, development and validation of advanced artificial intelligence solutions for the implementation of agentic systems based on LLMs, with particular reference to orchestration techniques and
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on analyzing economic dynamics and policies based on agent-based models. The selected researcher will be expected to adopt the most rigorous research methods, maintain relationships with both national and
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new generative AI models based on Model-Context Protocols and self-learning agents to analyze complex real-world scenarios in real time, particularly those involving cybersecurity challenges. It will
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cues play a role analogous to conditioned stimuli: they are signals that, once learned, allow the agent to anticipate the consequences of its actions. Scientific Motivation: Learning-based navigation
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for the fast adaptation of large vision-language agentic models, including supervised and reinforcement learning. The project team at HSP is responsible for all the phases of the research development and within