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Field
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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
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systems Reinforcement Learning and Agentic Control: Hands-on experience with reinforcement learning, multi-agent systems, or planning-based agents for autonomous vehicles or robots operating in dynamic
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bridge the fields of Generative AI, Recommendation System, Labor Economics/Organizational Science, and Social Simulation Platform. The key focus areas of this project include: 1. Agentic Career
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porous solids for the capture and/or degradation of toxic agents (or simulants) and sensors. Main activities Identification of MOFS composition Using existing databases that have already identified
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demand, or robotic agents to coupled tasks), where interactions and coordination requirements between entities—such as connecting passengers, pooled service requests, customer time windows, and robotic
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year, with the possibility of renewal for a second year based on satisfactory progress as outlined in the scholar’s Individual Development Plan (IDP). The Computational Neuropsychology & Simulation (CNS
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the possibility of renewal for a second year based on satisfactory progress as outlined in the scholar’s Individual Development Plan (IDP). The Computational Neuropsychology & Simulation (CNS ) Lab and Dr. Thomas D
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online support platforms (e.g., 7Cups), we are developing prototypes that use LLM and conversational agents to deliver scalable, experiential micro-skills training (such as empathy, active listening, and
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using gem5 simulator as the main execution backend for the RL agent, while also investigating the potential of RTL simulation and physical RISC-V board as complementary execution nvironments. A key aspect
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integrates real-time data and simulation models to mirror the physical manufacturing and logistics systems. This enables performance monitoring, predictive analysis, and the evaluation of scheduling strategies