Case study

TempleRun-RL: reconstructing Temple Run mechanics for simulator training

TempleRun-RL reconstructs Temple Run's track generation, hazards, and runner physics in a headless training simulator. A Frida gadget reads live state and calls game methods on an arm64 Android phone so the project can measure behavior and evaluate a PPO policy against the original. The author reports a longest device run of 16,782 metres.

Targets: Game
Category: Independent reconstruction cases
Relationship: Independent reconstruction project
Sources reviewed: 2026-11-06
Evidence class: C2 code & docs, no demo or download

Stars: 4
Last commit: 2026-10-15
Language: Python

GitHub data as of 2026-11-10

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Evidence

Observed: Code, documentation and a demo observed; no download method found.
Checked: 2026-11-08

How evidence classes are assigned

Requirements & limits

Prerequisites: A non-rooted arm64 Android phone with USB debugging, adb, and a user-supplied Temple Run v1.39.0 APK are required for device evaluation.
Prerequisites: The APK must be patched with a Frida gadget; the game is not included.
Testing evidence: The C++ simulator was developed and tested on Windows only.
License: Licensed under MIT.

Cite

BibTeX

@misc{templerun-rl-case,
  title = {{TempleRun-RL: reconstructing Temple Run mechanics for simulator training}},
  howpublished = {\url{https://github.com/matthieucs/TempleRun-RL}},
  url = {https://github.com/matthieucs/TempleRun-RL},
  urldate = {2026-11-06},
  note = {Awesome REA entry: \url{https://awesomerea.org/resources/templerun-rl-case/}}
}

Plain text

TempleRun-RL: reconstructing Temple Run mechanics for simulator training. https://github.com/matthieucs/TempleRun-RL (accessed 2026-11-06). Awesome REA entry: https://awesomerea.org/resources/templerun-rl-case/

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Primary sources

README.md GitHub · matthieucs/TempleRun-RL · Revision ca34ece
docs/GADGET.md GitHub · matthieucs/TempleRun-RL · Revision ca34ece