# Earning Mechanisms ### HTE Tokenomic's Reward System The HTE earning mechanism will **evolve through distinct stages**, aligning with the ecosystem's maturation and growth. Market stabilization and precise solution adaptation necessitate a phased approach. Currency price stability introduces inherent costs and challenges throughout this process (Yale Univeresity, Federal Reserve Bank of NY, 2011) . First stage will be to monitor and operate individual earnings and each will have its own efffort/reward rations or earnings by "actions". Then it will move onto **Unified Effort to Reward Algorithm (Scalable Standardization)** for scalability and automation. **Then more progressive approach towards Dynamic Reward Adjustment Method** combined with a **Stamina/Daily Cap Mechanism** to ensure fair token distribution across different applications within the HTE ecosystem. This system prevents reward farming inefficiencies and creates an adaptable model for future expansion, including AI-driven real-time adjustments.

Reward System Diagram

### Key Challenges * Different apps have varying levels of effort-to-reward ratios, leading users to choose the easiest method to earn HTE. * The ecosystem needs a **scalable** reward mechanism that remains **fair and adaptable**. * Preventing over-exploitation while encouraging **balanced engagement** across all platforms. ### **Unified Effort-to-Reward Algorithm (Scalable Standardization)** **This will be the first and foremost approach that HTE will take from initial manually configured reward ratio** - which will be the simplest and easiest way for the community and operations - but still has above mentioned [Key Challenges](#key-challenges) to be considered. Instead of manually adjusting each app’s reward rate, create a formula that calculates HTE rewards dynamically based on: • Effort/time spent • Engagement difficulty • Market demand for each app’s rewards Example Formula: $$ HTE\_{\text{earned}} = \frac{E\_{\text{effort}} \times B\_{\text{difficulty}}}{R\_{\text{supply}}} $$ Where: • E= effort/time required • B = difficulty multiplier (higher for harder tasks) • R = real-time balancing factor (adjusts if too many people farm one app) Whenever anew app(s) or method(s) is/are added, it automatically fits into this framework instead of requiring manual adjustments. ### Dynamic Reward Adjustment Mechanism Rewards are adjusted based on real-time user engagement and effort metrics. The **base unit of reward calculation** is set at **with base numerals(e.g. 1 or 0.1)**, which will be manually converted into HTE by the project team based on market conditions. #### Core Formula for Dynamic Reward Adjustment given: * **E\_effort** = Effort Score based on engagement metrics * **B\_difficulty** = Base difficulty of the task * **R\_supply** = Reward supply adjustment factor based on user demand * **P\_app** = Participation weight (number of users engaged in the app) $$ HTE\_{\text{earned}} = \frac{E\_{\text{effort}} \times B\_{\text{difficulty}}}{R\_{\text{supply}} \times P\_{\text{app}}} \ $$ where: * Higher **E\_effort** increases reward per task. * Higher **P\_app** decreases rewards per user to balance supply. * **R\_supply** adjusts dynamically to prevent excessive inflation. #### Dynamic Scaling Based on User Engagement To prevent excessive farming of a single app, **R\_supply** is dynamically adjusted using: $$ R\_{\text{supply}} = 1 + \alpha (U\_{\text{max}} - U\_{\text{current}}) \ $$ where: * **U\_max** = Maximum optimal user base per app * **U\_current** = Active users in the app * **\alpha** = Sensitivity constant for supply adjustment ### Stamina & Daily Cap Mechanism The Stamina & Daily Cap system prevents players from excessively earning HTE beyond a reasonable effort threshold. #### Stamina Calculation * Each player starts with a fixed **Stamina Pool (S\_max)** per day. * Actions consume stamina points (S\_consume) based on difficulty. $$ S\_{\text{remaining}} = S\_{\text{max}} - \sum S\_{\text{consume}} $$ * Once **S\_remaining = 0**, the player stops earning HTE until reset. #### Daily Cap Implementation A global daily cap ensures sustainable token distribution: $$ HTE\_{\text{daily}} \leq \beta \times (\sum U\_{\text{total}}) $$ where: * **HTE\_daily** = Maximum HTE distributed per day * **\beta** = Fixed multiplier based on supply control * **U\_total** = Total active users in the ecosystem ### Future Expansion & AI Integration Future iterations will include an **Effort-to-HTE Formula (Weight-Based Approach)** for finer reward balancing, followed by **AI or Machine Learning models** to automate real-time adjustments. ### Conclusion This presents HTE's tokenomics, especially the mechanism dynamics by stage as the time goes by, from various methods including basic to unified, dynamic, scalable solution for HTE token rewards, ensuring fairness and adaptability across multiple applications. The team will manually convert the base reward unit (base numerals like 1 or 0.1) into HTE based on market conditions, allowing precise control over the token economy. --- # 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://hederatoearn.gitbook.io/whitepaper/hte-tokenomics/introducing-hte/earning-mechanisms.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.