AI agent optimizes market prices for sustainability and fairness

This research paper proposes a novel approach using deep reinforcement learning to set market prices that account for externalities and sustainability. The proposed policymaker agent operates within an environment of other learning agents, allowing for the adjustment of prices based on various objectives like resource wastefulness, fairness, and overall welfare. Notably, the policymaker demonstrated superior performance in maintaining resource sustainability in scarce environments compared to traditional market equilibrium outcomes. AI

IMPACT Introduces a potential method for internalizing externalities in market economies, which could lead to more sustainable resource allocation.

RANK_REASON Research paper published on arXiv detailing a novel AI approach. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

• arXiv
• deep reinforcement learning
• Panayiotis Danassis

• paper
• other

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