High-Value Project Tutorials
Beat The Retention! Not The Algorithm!
Keep Players, Grow Your Game, Forget Competitors!
Make Games That Adapts To Players, Not The Other Way Around!
And Keep The Source Of Retention And Revenue Out Of Competitors’ Sight!
Disclaimer
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References that validates the use cases can be found here. It also includes my papers.
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The “minimal implementation time” assumes that a junior gameplay machine learning engineer is handling the implementation.
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Since DataPredict is written in native Lua, you can have extra compute per player alongside a single Roblox server by loading the models on players’ Roblox client.
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Phone users: Likely have 4 GB - 8 GB RAM. Variable CPU.
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PC users: Likely have 8 GB - 16 GB RAM. Variable CPU.
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Before you engage in integrating machine, deep and reinforcement learning models into live projects, I recommend you to have a look at safe practices here.
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The content of this page and its links are licensed under the DataPredict™ library’s Terms And Conditions. This includes the codes shown in the links below.
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Therefore, creating or redistributing copies or derivatives of this page and its links’ contents are not allowed.
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Commercial use is also limited unless you have a separate license from me.
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You can download and read the full list of commercial licensing agreements here.
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For information regarding potential license violations and eligibility for a bounty reward, please refer to the Terms And Conditions Violation Bounty Reward Information.
Links
| System | Properties | Minimal Implementation Time |
|---|---|---|
| Retention | Handles play time maximization and leave predictions. | 30 minutes - 6 hours |
| Recommendation | Improves the likelihood of selling items. | 2 hours |
| Dynamic Difficulty Adjustment | Ensures that the player is likely to interact with the enemies. | 30 minutes - 2 hours |
| AI Player | Replace players if players aren’t enough. | 30 minutes - 1 hour |
| Team Balancing | Ensures that teams are balanced based on their combat data. | 30 minutes |
| Anti-Cheat | Handles the separation of unusual players from normal players without changing the game mechanics. | 30 minutes |
| Targeting | Maximizes the likelihood of hitting clusters of players. | 30 minutes - 1 hour |
| Priority (Incomplete) | Making sure that the players or items are queued based on their data. | To be added soon |
| Placement | Finds an empty space to place players or items. | 30 minutes |
| Quality Assurance (Incomplete) | Attempts to break game mechanics to find edge cases and exploits. | To be added soon |