🧪 Test?View on arXiv
PAWS: Policy-driven Agentic World Simulation
Not specified in the provided content
financial simulationpolicy analysismulti-agent systems
2609.28547
Builder Relevance
1h ago70%
Abstract
PAWS introduces a dataset that connects financial policy interventions to historical evidence through multi-agent simulations.
Reality Card
Core Claim
PAWS provides a comprehensive dataset linking policy interventions to stakeholder actions and market responses, enabling accurate simulations of financial policies.
Method / Result
Independent AI and human reviewers achieved 89.4% initial agreement on interaction mode from 2,522 stratified action samples.
Limitations
High accuracy may mask the failure to detect rare stakeholder actions, highlighting challenges in action timing and calibration.
Paper to code
Verified implementation resources so builders can test the paper’s claims instead of stopping at the abstract.
No verified implementation link has been attached yet. AIBuzzHub will keep this panel separate from unverified search results.