世界-地球系统模型中的深度强化学习，以发现可持续管理策略
Deep reinforcement learning in World-Earth system models to discover sustainable management strategies
摘要：
越来越复杂的非线性世界-地球系统模型用于描述生物物理地球系统和人类社会的社会经济和社会文化世界及其相互作用的动态。在这些模型中确定通往可持续未来的途径，以便为决策者和广大公众提供信息，例如，导致有力缓解危险的人为气候变化的途径，是气候研究和更广泛的地球系统科学领域中一项具有挑战性和广泛研究的任务。当需要考虑到对避免超越地球界限和社会基础的限制时，这个问题就特别困难。在这项工作中，我们建议将最近开发的机器学习技术，即深度强化学习（DRL），与世界-地球系统中轨迹的经典分析相结合。基于代理环境接口的概念，我们开发了一个代理，通常能够在地球系统的可变可管理环境模型中采取行动和学习。我们证明了我们的框架的潜力，通过应用DRL算法两个程式化的世界地球系统模型。从概念上讲，我们探索找到新的全球治理政策的可行性，从而导致一个安全和公正的运作空间，受到某些行星和社会经济界限的限制。人工智能代理了解到，对碳排放征税和对可再生能源补贴的具体组合的时机对于寻找长期可持续的世界地球系统轨迹至关重要。
英文摘要：
Increasingly complex, non-linear World-Earth system models are used for describing the dynamics of the biophysical Earth system and the socio-economic and socio-cultural World of human societies and their interactions. Identifying pathways towards a sustainable future in these models for informing policy makers and the wider public, e.g. pathways leading to a robust mitigation of dangerous anthropogenic climate change, is a challenging and widely investigated task in the field of climate research and broader Earth system science. This problem is particularly difficult when constraints on avoiding transgressions of planetary boundaries and social foundations need to be taken into account. In this work, we propose to combine recently developed machine learning techniques, namely deep reinforcement learning (DRL), with classical analysis of trajectories in the World-Earth system. Based on the concept of the agent-environment interface, we develop an agent that is generally able to act and learn in variable manageable environment models of the Earth system. We demonstrate the potential of our framework by applying DRL algorithms to two stylized World-Earth system models. Conceptually, we explore thereby the feasibility of finding novel global governance policies leading into a safe and just operating space constrained by certain planetary and socio-economic boundaries. The artificially intelligent agent learns that the timing of a specific mix of taxing carbon emissions and subsidies on renewables is of crucial relevance for finding World-Earth system trajectories that are sustainable on the long term.
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