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arXiv 2402.09563cs.MAecon.GNq-fin.EC
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ABIDES-Economist:具有学习智能体的经济系统基于智能体的模拟器

ABIDES-Economist: Agent-Based Simulator of Economic Systems with Learning Agents

Kshama Dwarakanath, Tucker Balch, Svitlana Vyetrenko

AI总结:

提出ABIDES-Economist经济系统模拟器,集成强化学习智能体并基于真实数据校准,验证其能复现微观与宏观经济程式化事实,并优于传统规则方法设计监管政策。

摘要:

我们提出了ABIDES-Economist,一个用于经济系统的基于智能体的模拟器,包含异质家庭、企业、中央银行和政府。智能体行为可以通过特定领域的规则定义,或者通过指定其目标并利用强化学习来学习。我们使用OpenAI Gym环境框架为多智能体系统集成了所有智能体的强化学习能力。为了增强模型的真实性,我们基于经济学文献和真实的美国经济数据来设定智能体参数和动作空间。为了解决校准异质智能体经济模型的挑战,我们对与微观和宏观经济时间序列数据相关的程式化事实进行了全面调查。随后,在通过强化学习所有智能体行为之后,我们通过展示其生成与所考虑的经济场景的相关程式化事实相一致的模拟数据的能力,验证了ABIDES-Economist。具体而言,我们在两种广泛配置下训练经济智能体的策略。第一种配置表明,学习到的经济智能体产生的系统数据与宏观经济和微观经济程式化事实相一致。第二种配置说明了验证后的仿真平台在设计中央银行和政府的监管政策方面的效用。这些政策优于文献中标准的基于规则的方法,后者通常忽略了智能体异质性、冲击和智能体适应性。

英文摘要:

We present ABIDES-Economist, an agent-based simulator for economic systems that includes heterogeneous households, firms, a central bank, and a government. Agent behavior can be defined using domain-specific behavioral rules or learned through reinforcement learning by specifying their objectives. We integrate reinforcement learning capabilities for all agents using the OpenAI Gym environment framework for the multi-agent system. To enhance the realism of our model, we base agent parameters and action spaces on economic literature and real U.S. economic data. To tackle the challenges of calibrating heterogeneous agent-based economic models, we conduct a comprehensive survey of stylized facts related to both microeconomic and macroeconomic time series data. We then validate ABIDES-Economist by demonstrating its ability to generate simulated data that aligns with the relevant stylized facts for the economic scenario under consideration, following the learning of all agent behaviors via reinforcement learning. Specifically, we train our economic agents' policies under two broad configurations. The first configuration demonstrates that the learned economic agents produce system data consistent with macroeconomic and microeconomic stylized facts. The second configuration illustrates the utility of the validated simulation platform in designing regulatory policies for the central bank and government. These policies outperform standard rule-based approaches from the literature, which often overlook agent heterogeneity, shocks, and agent adaptability.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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