> For the complete documentation index, see [llms.txt](https://olaxbt-docs.gitbook.io/olaxbt-doc/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://olaxbt-docs.gitbook.io/olaxbt-doc/project-info/olaxbt-agent/chat-to-earn/reinforcement-learning.md).

# Reinforcement Learning

We encourage users to actively utilise credits to unlock the full potential of the credit utilities. 

By spending credits on AI-driven tools like AI Market Maker Analysis, Whale Tracking, and Trading Signals, users gain valuable market insights to stay ahead in crypto trading. 

<figure><img src="/files/xeeH63sGMc8IQ6vs5qop" alt=""><figcaption></figcaption></figure>

For example, a Core Pro user spending 2,000 credits earns 300 score (0.15 score per message). <br>

These earned score, combined with purchased and referral credits, amplify your access to premium tools. The more you engage and spend, the more you benefit, creating a cycle of learning and reward to optimise your trading strategy.

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