> 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

Maximize benefit with earned, purchased, and referral credits for more tool access.

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="https://3556351364-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2Ft8OGZsVW8nFWE4BbjRiz%2Fuploads%2FLFDqJjRvJM1YLGn0qBMd%2FReinforcement%20Learning.png?alt=media&amp;token=dec87060-5502-4901-8736-b4dcee99ca25" 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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