TL;DR: Deep reinforcement learning (RL), a powerful learning framework to train AI agents, can be slow as it requires repeated interaction with a simulation of the environment. Our original WarpDrive accelerates multi-agent deep RL on NVIDIA GPUs, enabling 10-100x speedups compared to alternative CPU+GPU implementations of multi-agent simulations.

TL;DR:  Salesforce Research and Mila announce AI for Global Climate Cooperation, a working group collaboration and competition to design negotiation protocols and climate agreements. We plan to coauthor a peer-reviewed scientific paper with top-performing teams; insights will be distilled into a policy brief shared with leading policymakers, informing future

TL;DR: WarpDrive is a flexible, lightweight, easy-to-use end-to-end reinforcement learning (RL) framework; enables orders-of-magnitude faster training on a single GPU. PyTorch Lightning enables you to modularize experimental code, and build production-ready workloads fast. Together, they can help significantly accelerate multi-agent RL R&D. Reinforcement Learning: Agents Learn by

TL;DR: The AI Economist, a reinforcement learning (RL) system, learns dynamic tax policies that optimize equality along with productivity in simulated economies, outperforming alternative tax systems. We have now expanded this research, which is being published in the interdisciplinary scientific journal Science Advances. Humans or AI: Which Can Design

tldr: WarpDrive is an open-source framework to do multi-agent RL end-to-end on a GPU. It achieves orders of magnitude faster multi-agent RL training with 2000 environments and 1000 agents in a simple Tag environment. WarpDrive provides lightweight tools and workflow objects to build your own fast RL workflows. Check out

This blog accompanies the interactive demo [https://einstein.ai/the-ai-economist/ai-policy-foundation-and-covid-case-study] and paper [https://arxiv.org/abs/2108.02904]! Dive deeper into the underlying simulation code [https://www.github.com/salesforce/ai-economist ] and simulation card [https://github.com/salesforce/ai-economist/blob/master/COVID-19_Simulation-Card.pdf] . In this blog post, we

We recently released Foundation, an open-source framework [https://github.com/salesforce/ai-economist] to build economic simulations. Foundation has been designed with flexibility and AI research in mind, and can be modified by anyone. AI simulations offer researchers the power to generate data and evaluate outcomes of virtual economies that capture

We are launching an open source collaborative project to build an AI Economist that can be used to guide policy making in the real world. We invite you to join us in our mission to help improve the world with AI and economics.

In this work, we focus on the opportunity to use AI to promote social welfare through the design of optimal tax policies in dynamic economies.