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1
Introduction
2
What is this research
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Why AI
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Economic Inequality
5
History of Tax Theory
6
Questions
7
The Spatial World
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LowLevel Details
9
Assumptions
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Simulation
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Agents
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Deep Behavioral Parameters
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Why a Simplified Setting
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Specialization
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Communication
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RL
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Government
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Optimality
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Mechanism Design
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Income Taxes
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Deep Learning
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Two Level Learning
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Mitigating Instability
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Multiagent Learning
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SidebySide Comparison
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Tax Models
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Elasticity
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Strategic
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Testing
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Measuring Equality
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Other Measures of Equality
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How AI Economists Respond to Shocks
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Conceptual Question
Description:
Explore groundbreaking research on AI-driven tax policies in this Simons Institute lecture from the Theory of Reinforcement Learning Boot Camp. Delve into the concept of the AI Economist, examining how artificial intelligence can be leveraged to improve equality and productivity through innovative tax strategies. Learn about economic inequality, the history of tax theory, and the application of reinforcement learning in economic simulations. Discover the intricacies of a spatial world model, including agent behavior, specialization, and communication. Investigate the role of deep learning in optimizing government policies, mechanism design, and income taxes. Compare various tax models, explore measures of equality, and understand how AI economists respond to economic shocks. Gain insights into the potential of AI to reshape economic policy and address real-world challenges in wealth distribution and productivity.

The AI Economist- Improving Equality and Productivity with AI-Driven Tax Policies

Simons Institute
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