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operators for these notions. Over the past fifty years, such non-classical logics have proved vital in computer science and logic-based artificial intelligence: after all, any intelligent agent must be able
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simulation, including O/D modeling, multimodal network modeling, agent-based or behavioral modeling Large-scale computing, cloud-native analytics workflows, and data engineering for mobility platforms AI/ML
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learning with knowledge-based inference, validated by independent experiments and partially supervised by human-in-the-loop systems. A key question will be how agentic AI and foundation models can be
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-Service (MaaS) ecosystem. The work will integrate deep reinforcement learning, autonomous agent modelling, and multi-objective optimization to enable predictive simulation, real-time resource management
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modeling and coordination of interdependent infrastructure systems and their subsystems (such as networks of transportation, gas, electricity grid), multi-agent reinforcement learning for distributed
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contrast, analysis of systemic risks embraces complex interactions among elements/agents, adjusting expectations, mechanisms of contagion dynamics, feedbacks, and non-linear tipping. The SPHINX research
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the Patient Registration Patient Intake, and Patient Relations offices, Simulation Clinic and Labs, Central Sterilization, and two dispensaries. OCS supports the operations of 13 dental clinics in delivering
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Scholarships. Institutional Programs: NSE, Institutional Grants, Institutional Scholarships, private loans, private scholarships, private programs. Acts as a change agent in all matters regarding the improvement
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controlled drugs, intravenous solutions, antibiotics, and other agents used to treat medical problems. Anticipates and recognizes deviations from normal infant deliveries and institutes procedures designed
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of systemic risks embraces complex interactions among elements/agents, adjusting expectations, mechanisms of contagion dynamics, feedbacks, and non-linear tipping. The SPHINX research program aims