MALLES: A Multi-agent LLMs-based Economic Sandbox with Consumer Preference Alignment
In the real economy, modern decision-making is fundamentally challenged by high-dimensional, multimodal environments, which are further complicated by agent heterogeneity and combinatorial data sparsity. This paper introduces a Multi-Agent Large Language Model-based Economic Sandbox (MALLES), leveraging the inherent generalization capabilities of large-sacle models to establish a unified simulation framework applicable to cross-domain and cross-category scenarios. Central to our approach is a pr
Record details
Published: 18 March 2026
Source: arXiv
Category: Research
Topics: Safety & alignment · Jobs & economy · Agents & autonomy · Environment
Retrieved: 14 July 2026
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ethics.ai (18 March 2026), “MALLES: A Multi-agent LLMs-based Economic Sandbox with Consumer Preference Alignment,” evidence record 7066, https://ethics.ai/record/7066 (originally published by arXiv).
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