no code implementations • 10 Jul 2023 • Yoshua Bengio, Prateek Gupta, Lu Li, Soham Phade, Sunil Srinivasa, Andrew Williams, Tianyu Zhang, Yang Zhang, Stephan Zheng
On the other hand, an interdisciplinary panel of human experts in law, policy, sociology, economics and environmental science, evaluated the solutions qualitatively.
2 code implementations • 15 Aug 2022 • Tianyu Zhang, Andrew Williams, Soham Phade, Sunil Srinivasa, Yang Zhang, Prateek Gupta, Yoshua Bengio, Stephan Zheng
To facilitate this research, here we introduce RICE-N, a multi-region integrated assessment model that simulates the global climate and economy, and which can be used to design and evaluate the strategic outcomes for different negotiation and agreement frameworks.
3 code implementations • 31 Aug 2021 • Tian Lan, Sunil Srinivasa, Huan Wang, Stephan Zheng
We present WarpDrive, a flexible, lightweight, and easy-to-use open-source RL framework that implements end-to-end deep multi-agent RL on a single GPU (Graphics Processing Unit), built on PyCUDA and PyTorch.
1 code implementation • 6 Aug 2021 • Alexander Trott, Sunil Srinivasa, Douwe van der Wal, Sebastien Haneuse, Stephan Zheng
Here we show that the AI Economist framework enables effective, flexible, and interpretable policy design using two-level reinforcement learning (RL) and data-driven simulations.
1 code implementation • 5 Aug 2021 • Stephan Zheng, Alexander Trott, Sunil Srinivasa, David C. Parkes, Richard Socher
Here we show that machine-learning-based economic simulation is a powerful policy and mechanism design framework to overcome these limitations.
2 code implementations • 28 Apr 2020 • Stephan Zheng, Alexander Trott, Sunil Srinivasa, Nikhil Naik, Melvin Gruesbeck, David C. Parkes, Richard Socher
In experiments conducted on MTurk, an AI tax policy provides an equality-productivity trade-off that is similar to that provided by the Saez framework along with higher inverse-income weighted social welfare.
no code implementations • 3 Jan 2017 • Nithyanand Kota, Abhishek Mishra, Sunil Srinivasa, Xi, Chen, Pieter Abbeel
The high variance issue in unbiased policy-gradient methods such as VPG and REINFORCE is typically mitigated by adding a baseline.