@xiaoxuanh.bsky.social
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xiaoxuanh.bsky.social
For details, check out @yuanjiayi.bsky.social post and our full paper. If you're interested in learning more or collaborating, reach out! 🚀 #AI #ESG #ReinforcementLearning (6/6)
xiaoxuanh.bsky.social
With an ESG disclosure mandate, mitigation boosts ESG scores, helping attract ESG-conscious investors. However, companies can also greenwash—faking ESG efforts at a lower cost. Our existing simulations have already uncovered interesting dynamics! (5/6)
xiaoxuanh.bsky.social
By default, climate risk worsens over time, increasing the chance of disasters that harm all companies. Without an ESG disclosure mandate, companies can mitigate risk, reducing climate threats for all—but at a cost. (4/6)
xiaoxuanh.bsky.social
(1) Mirror how key decision-makers behave in the real world
(2) Identify flaws in alternative policy designs
(3) Discover sophisticated cooperation strategies beyond human intuition
How did we build our MARL environment? (3/6)
xiaoxuanh.bsky.social
Supporters argue an ESG mandate increases transparency and accountability. Opponents fear it raises costs and stifles business growth. We believe RL & MARL communities can help inform such policy debates by designing AI agents that: (2/6)
xiaoxuanh.bsky.social
AI has shown great potential in boosting efficiency. But can it help human society make better decisions as a whole? 🤔 In this project, using MARL, we explore this by studying the impact of an ESG disclosure mandate—a highly controversial policy. (1/6)
yuanjiayi.bsky.social
In our latest work, we introduce InvestESG, a lightweight, GPU-efficient MARL environment, designed to study incentives surrounding corporate climate mitigation and climate risks. Check out the project website: sites.google.com/view/investe...
InvestESG
TLDR: We introduce InvestESG, a lightweight, GPU-efficient MARL environment simulating company and investor responses to ESG disclosure mandates, with companies and investors modeled as two types of s...
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