Discussing the article: "Using Deep Reinforcement Learning to Enhance Ilan Expert Advisor"

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Check out the new article: Using Deep Reinforcement Learning to Enhance Ilan Expert Advisor.

We revisit the Ilan grid Expert Advisor and integrate Q-learning in MQL5 to build an adaptive version for MetaTrader 5. The article shows how to define state features, discretize them for a Q-table, select actions with ε-greedy, and shape rewards for averaging and exits. You will implement saving/loading the Q-table, tune learning parameters, and test on EURUSD/AUDUSD in the Strategy Tester to evaluate stability and drawdown risks.

In this article, we challenge established ideas about trading systems and undertake an ambitious attempt to revive classic Ilan by equipping it with deep reinforcement learning (DQN) mechanisms and a dynamic Q-table. We are not just modifying existing code, we are creating a fundamentally new intelligent system capable of learning from our own experience, adapting to market changes and optimizing trading solutions in real time.

Our journey will take you through the labyrinths of algorithmic trading, where mathematical rigor meets computational elegance, and classic Martingale techniques take on new life thanks to innovative machine learning approaches. Whether you are an experienced algorithmic trader, a trading system developer, or just a financial technology enthusiast, this article offers a unique perspective on the future of automated trading.

Fasten your seat belts — we are embarking on an exciting journey to create Ilan 3.0 AI, where tradition meets innovation, and the past evolves into the future.


Author: Yevgeniy Koshtenko

 

I've read it briefly - at first glance the article is super!

it is necessary to watch and test on different symbols - which ones are better and which ones are worse to be trained by ilano!

 

Martin owes a lot.

It will be interesting to get an advanced product with a development perspective.

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