Automated Market Maker

Automated market makers (AMMs) are algorithms that automatically provide liquidity in decentralized exchanges, aiming to optimize trading efficiency and profitability for both the market maker and liquidity providers. Current research focuses on improving AMM design through advanced algorithms like reinforcement learning (including Q-learning and LSTM networks), Bayesian methods, and optimal transport theory, often incorporating external price data to mitigate risks like impermanent loss and arbitrage. These advancements are crucial for enhancing the stability and efficiency of decentralized finance (DeFi) ecosystems and improving the overall trading experience for users.