Cooperative Multi-Agent Reinforcement Learning for Market Making on Prediction-Market Order Books
Paper recorded by Signals 4 on 2026-10-19 in cs.LG. Abstract reproduced from arXiv; link to the original below.
Published 2026-10-19 on arXiv · recorded by Signals 4 on 2026-10-20
Category: cs.LG · 机器学习 · first seen 2026-10-20
Abstract
A market maker provides liquidity by quoting prices to buy and sell an asset, earning the spread while managing inventory risk. We study market makers trained with multi-agent reinforcement learning on prediction markets, specifically Polymarket, whose thin order books pose distinct challenges. Three challenges underpin this research: adverse selection may cause a policy trained on real data to st
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Cite this page: Cooperative Multi-Agent Reinforcement Learning for Market Making on Prediction-Market Order Books: the #244 most recent of 749 cs.LG papers we have recorded (as of 2026-10-19). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/cooperative-multi-agent-reinforcement-learning-for-market-making-on-prediction-m.html
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