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developments in agentic AI. This means that you are expected to stay up to date with research on LLM-based agents, prompting methods, fine-tuning strategies, and multi-agent systems, and to assess how
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argumentative agentic AI approach for chemical development settings based on reinforcement learning but able to shape rewards with the help of ontological knowledge as well as expert knowledge from humans and
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identification of optimization levers while ensuring compliance with safety requirements. The work will be based on process and decision modeling standards (notably BPMN and DMN), enhanced by agent-based AI
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the creation of realistic simulated environments based on environmental data. - Defining evaluation protocols and performance metrics (safety, energy, mission efficiency). - Contributing to scientific validation
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diverse spanning ancient urban systems, historical records, and contemporary political and social data · Contributing to the design and implementation of agent-based simulation models and computational
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simulations, so that they maintain their validity. The process consists in evaluating a sequence of overlapping mental simulations to construct the future course of actions that the agent will take, based
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Your Job: In this master thesis, a multi-agent-based local energy market simulation ASSUME shall be extended to account for district grid constraints. The objective is to investigate how local grid
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of cell factory engineering. Develop software tools that enable programmatic interaction between large language model agents and metabolic models, enabling automated simulation, interpretation, and
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(Lua/Java), agent behavior modeling, event handling, and API-based integration with external AI systems. Experience with distributed systems, reinforcement learning, or simulation environments (e.g
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, and can analogous mechanisms be engineered into multi-agent AI systems? You would answer this question by building and testing computational models, developing multi-agent simulations where agents