AI Research
PAWS: Policy-driven Agentic World Simulation
Bridging historical evidence and financial simulation for smarter policy testing.
Policy interventions propagate through public communication, institutional decisions, and stakeholder responses, yet datasets for financial multi-agent simulation rarely connect these processes to temporally aligned historical evidence. We introduce PAWS, a Policy-driven Agentic ...
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ArXiv CS.AI
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ArXiv CS.AI
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Generated insight by OnAirToday AI
PAWS bridges the critical gap between abstract financial simulations and real-world policy outcomes by grounding agentic behavior in verifiable historical data. This research provides a robust framework for policymakers to stress-test economic interventions in a dynamic, high-fidelity environment.
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