The AI Economist: Taxation policy design via two-level deep reinforcement learning

Stephan Zheng, Alexander Trott, Sunil Srinivasa, David Parkes & Richard Socher
This dataset contains all raw experimental data for the paper "The AI Economist: Taxation Policy Design via Two-level Deep Multi-Agent Reinforcement Learning". The accompanying simulation, reinforcement learning, and data visualization code can be found at https://github.com/salesforce/ai-economist. For the one-step economy experiments, we provide: training histories, configuration files (these experiments do not use phases), and final agent and planner models. For the Gather-Trade-Build scenario, the data covers 6 spatial layouts: two Open-Quadrant (with 4 and 10...
1 citation reported since publication in 2021.
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