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the MATSim agent-based transport simulation framework. The main task is to enable simulated agents to choose transportation modes, such as car, bus, bike, or walking, based on real-time feedback from
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. Specific projects seeking applications are: Accelerating the discovery of inorganic solar-cell materials via a closed-loop, fully robotic synthesis–characterisation platform driven by multi-agent machine
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to characterize network-wide interventions, like reallocating road space or travel demand management schemes. Second, to develop an MFD-based traffic simulation linked to the agent-based simulation environment
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/ Robust) Combinatorial Optimization, Game Theory, and Network Theory, as well as Artificial Intelligence. Potentially, scenarios could be simulated using agent-based, discrete-event, or other techniques
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employment. Please indicate the request in your application. Tasks: scientific research and development activities in the field of agent-based traffic modeling and simulation, e.g. on scenarios of sustainable
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to efficiently navigate high-dimensional decision spaces, leveraging open-source agent-based simulation tools to evaluate accessibility and environmental impacts of urban planning policies. You should have an MSc
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(a) networked multi-agent human-robotic systems that work collaboratively in a well-coordinated and safe manner, (b) computational design and digital manufacturing of components, (c) design of
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modification of the environment and content — creating a closed-loop learning system. Human-Robot Interaction (HRI): The learning environment may include robotic agents that interact with the learner. Here