Exploring the interplay between Planetary Boundaries and Sustainable Development Goals using Large Language Models

• URL: http://arxiv.org/abs/2509.02638v1
• Date: Mon, 01 Sep 2025 20:55:55 GMT
• Title: Exploring the interplay between Planetary Boundaries and Sustainable Development Goals using Large Language Models
• Authors: Lamyae Rhomrasi, Pilar Manchón, Ricardo Vinuesa, Francesco Fuso-Nerini, J. Alberto Conejero, Javier García-Martínez, Sergio Hoyas,
• Abstract summary: We identify interactions between Planetary Boundaries and Sustainable Development Goals.<n>Key findings include conflicts between land-use goals and land system boundaries.<n>Our study highlights the need for integrated policies that align development goals with planetary limits.
• Score: 3.443408730693827
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: By analyzing 40,037 climate articles using Large Language Models (LLMs), we identified interactions between Planetary Boundaries (PBs) and Sustainable Development Goals (SDGs). An automated reasoner distinguished true trade-offs (SDG progress harming PBs) and synergies (mutual reinforcement) from double positives and negatives (shared drivers). Results show 21.1% true trade-offs, 28.3% synergies, and 19.5% neutral interactions, with the remainder being double positive or negative. Key findings include conflicts between land-use goals (SDG2/SDG6) and land system boundaries (PB6), together with the underrepresentation of social SDGs in the climate literature. Our study highlights the need for integrated policies that align development goals with planetary limits to reduce systemic conflicts. We propose three steps: (1) integrated socio-ecological metrics, (2) governance ensuring that SDG progress respects Earth system limits, and (3) equity measures protecting marginalized groups from boundary compliance costs.

Related papers

• Distributed Causality in the SDG Network: Evidence from Panel VAR and Conditional Independence Analysis [0.0]
  Education to Inequality is identified as the most statistically significant direct relationship.<n>We offer a proposed tiered priority framework for the SDGs namely, identifying upstream drivers (Education, Growth), enabling goals (Institutions, Energy), and downstream outcomes (Poverty, Health)
  arXiv  Detail & Related papers  (2026-01-19T00:22:06Z)
• Learning Whole-Body Human-Humanoid Interaction from Human-Human Demonstrations [63.80827184637476]
  We introduce D-STAR, a hierarchical policy that disentangles when to act from where to act.<n>We validate our framework through extensive and rigorous simulations.
  arXiv  Detail & Related papers  (2026-01-14T14:37:06Z)
• BEDA: Belief Estimation as Probabilistic Constraints for Performing Strategic Dialogue Acts [69.7477004390211]
  We formalize two core acts Adversarial and Alignment, and operationalize them via probabilistic constraints on what an agent may generate.<n>We instantiate this idea in BEDA, a framework that consists of the world set, the belief estimator for belief estimation, and the conditional generator that selects acts and realizes utterances consistent with the inferred beliefs.
  arXiv  Detail & Related papers  (2025-12-31T14:26:55Z)
• Goal Discovery with Causal Capacity for Efficient Reinforcement Learning [85.28685202281918]
  Causal inference is crucial for humans to explore the world.<n>We propose a novel Goal Discovery with Causal Capacity framework for efficient environment exploration.
  arXiv  Detail & Related papers  (2025-08-13T08:54:56Z)
• The role of broadband connectivity in achieving Sustainable Development Goals (SDGs) [0.0]
  Recent studies have investigated the role of broadband in addressing the SDGs. We make four key recommendations on broadband sustainability research to fast-track achievement by 2030.
  arXiv  Detail & Related papers  (2024-10-31T00:24:32Z)
• Sustainable Visions: Unsupervised Machine Learning Insights on Global Development Goals [0.3764231189632788]
  The 2030 Agenda for Sustainable Development outlines 17 goals for countries of the world to address global challenges in their development.<n>We have used a novel data-driven methodology to analyze time-series data for over 20 years (2000-2022) from 107 countries using unsupervised machine learning (ML) techniques.<n>Our findings show that progress toward the SDGs is heavily influenced by geographical, cultural and socioeconomic factors.
  arXiv  Detail & Related papers  (2024-09-19T03:10:49Z)
• Variable-Agnostic Causal Exploration for Reinforcement Learning [56.52768265734155]
  We introduce a novel framework, Variable-Agnostic Causal Exploration for Reinforcement Learning (VACERL) Our approach automatically identifies crucial observation-action steps associated with key variables using attention mechanisms. It constructs the causal graph connecting these steps, which guides the agent towards observation-action pairs with greater causal influence on task completion.
  arXiv  Detail & Related papers  (2024-07-17T09:45:27Z)
• TrajPRed: Trajectory Prediction with Region-based Relation Learning [11.714283460714073]
  We propose a region-based relation learning paradigm for predicting human trajectories in traffic scenes. Social interactions are modeled by relating the temporal changes of local joint information from a global perspective. We integrate multi-goal estimation and region-based relation learning to model the two stimuli, social interactions, and goals, in a prediction framework.
  arXiv  Detail & Related papers  (2024-04-10T12:31:43Z)
• AI For Global Climate Cooperation 2023 Competition Proceedings [77.07135605362795]
  No global authority can ensure compliance with international climate agreements. RICE-N supports modeling regional decision-making using AI agents. The IAM then models the climate-economic impact of those decisions into the future.
  arXiv  Detail & Related papers  (2023-07-10T20:05:42Z)
• Byzantine-Robust Learning on Heterogeneous Data via Gradient Splitting [58.91947205027892]
  Federated learning has exhibited vulnerabilities to Byzantine attacks. Byzantine attackers can send arbitrary gradients to a central server to destroy the convergence and performance of the global model. A wealth of robust AGgregation Rules (AGRs) have been proposed to defend against Byzantine attacks.
  arXiv  Detail & Related papers  (2023-02-13T03:31:50Z)
• SustainBench: Benchmarks for Monitoring the Sustainable Development Goals with Machine Learning [63.192289553021816]
  Progress toward the United Nations Sustainable Development Goals has been hindered by a lack of data on key environmental and socioeconomic indicators. Recent advances in machine learning have made it possible to utilize abundant, frequently-updated, and globally available data, such as from satellites or social media. In this paper, we introduce SustainBench, a collection of 15 benchmark tasks across 7 SDGs.
  arXiv  Detail & Related papers  (2021-11-08T18:59:04Z)
• Learning to Plan Optimistically: Uncertainty-Guided Deep Exploration via Latent Model Ensembles [73.15950858151594]
  This paper presents Latent Optimistic Value Exploration (LOVE), a strategy that enables deep exploration through optimism in the face of uncertain long-term rewards. We combine latent world models with value function estimation to predict infinite-horizon returns and recover associated uncertainty via ensembling. We apply LOVE to visual robot control tasks in continuous action spaces and demonstrate on average more than 20% improved sample efficiency in comparison to state-of-the-art and other exploration objectives.
  arXiv  Detail & Related papers  (2020-10-27T22:06:57Z)
• Pandemic Lessons -- Devising an assessment framework to analyse policies for sustainability [0.0]
  COVID-19 pandemic has sharply projected the globally persistent multi-dimensional fundamental challenges in securing general socio-economic wellbeing of the society. These problems directly highlight the urgent need for accomplishing the interdependent United Nations Sustainable Development Goals. Using root cause analysis approach, we have developed a yearly assessment framework for viably analysing and identifying requisite region-specific downstream/upstream socio-economic policies.
  arXiv  Detail & Related papers  (2020-10-09T22:39:10Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.