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Improving International Climate Policy via Mutually Conditional Binding Commitments

arXiv 2307.14267 ↗First posted 26 Jul 2023cs.CY cs.AIcited by 1

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Abstract (arXiv)

The Paris Agreement, considered a significant milestone in climate negotiations, has faced challenges in effectively addressing climate change due to the unconditional nature of most Nationally Determined Contributions (NDCs). This has resulted in a prevalence of free-riding behavior among major polluters and a lack of concrete conditionality in NDCs. To address this issue, we propose the implementation of a decentralized, bottom-up approach called the Conditional Commitment Mechanism. This mechanism, inspired by the National Popular Vote Interstate Compact, offers flexibility and incentives for early adopters, aiming to formalize conditional cooperation in international climate policy. In this paper, we provide an overview of the mechanism, its performance in the AI4ClimateCooperation challenge, and discuss potential real-world implementation aspects. Prior knowledge of the climate mitigation collective action problem, basic economic principles, and game theory concepts are assumed.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 3 of its 16 references that are in the map. First posted on arXiv 26 Jul 2023.

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3 of 16 references.

References · 3

  1. 2017Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environmentscited by 108
  2. 2019Deep Reinforcement Learning for Tradingcited by 73
  3. 2022AI for Global Climate Cooperation: Modeling Global Climate Negotiations, Agreements, and Long-Term Cooperation in RICE-Ncited by 22

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