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I am a researcher with a strong theoretical basis in artificial intelligence. Specifically, reinforcement learning, combinatorial search, multiagent route assignment, game theory, flow and convex optimization, and multiagent modeling and simulation. I gained vast knowledge and experience in utilizing my theoretical foundations towards traffic management and traffic optimization application. Nonetheless, I view myself as part of the AI community where my work is highly cited. I strive to further the impact of my applicable expertise for solving real-life problems while simultaneously continuing to make theoretical advances that justify the proposed solutions.
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Michael Oesterle,Guni Sharon
ADVANCES IN ARTIFICIAL INTELLIGENCE, KI 2023no. 10 (2023): 252-256
arxiv(2023)
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AAMAS '23: Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systemspp.2134-2142, (2023)
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Building Simulation Conference Proceedings Proceedings of Building Simulation 2023: 18th Conference of IBPSA (2023)
arxiv(2022)
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