# Dynamic Reward System {% hint style="info" %} This system is subject to change as the game grows, and detailed information on any updates to the reward distribution process will be shared with the community. {% endhint %} The Dynamic Reward System is a core component of the game’s economic algorithms. It adjusts the rewards players receive from missions, quests, and other in-game activities based on various factors such as player activity, the number of active players, and the overall state of the in-game economy and token condition. * **Activity-Based Adjustments:** The algorithm monitors player activity levels/progression in real-time. If there is a surge in active players or completed missions, the algorithm may decrease the rewards to prevent inflation and ensure the token supply remains controlled. Conversely, if player activity drops, the system may increase rewards to incentivize participation. * **Token Supply Management:** By dynamically adjusting the number of tokens awarded through gameplay, the algorithm helps regulate the total supply of CTL tokens in circulation. This prevents an oversupply of tokens, which could devalue the currency, and maintains a healthy balance between token generation and spending. * **Difficulty Scaling:** The system also considers the difficulty of tasks when determining rewards. Harder tasks yield higher rewards, but the algorithm ensures that these rewards are proportional to the effort required, maintaining a balance between challenge and compensation. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://cto-io.gitbook.io/cyberton-land/technical-details/economic-algorithms/dynamic-reward-system.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.