Oxford U’s Deep Double Duelling Q-Learning Translates Trading Signals Into SOTA Trading Strategies | Synced
In the new paper Asynchronous Deep Double Duelling Q-Learning for Trading-Signal Execution in Limit Order Book Markets, an Oxford University research team introduces Deep Duelling Double Q-learning...
Source: Synced | AI Technology & Industry Review
In the new paper Asynchronous Deep Double Duelling Q-Learning for Trading-Signal Execution in Limit Order Book Markets, an Oxford University research team introduces Deep Duelling Double Q-learning with the APEX architecture to train a trading agent to translate predictive signals into optimal limit order trading strategies.