王者荣耀AI (Reinforcement Learning King of Glory AI) resource

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1829 stars · 411 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A PyTorch-based AI that plays the mobile game Honor of Kings (王者荣耀), built with a Resnet101 vision encoder plus a GPT/Transformer decoder, trained on recorded gameplay data. The original ResnetGPT project is no longer updated and has been superseded by a reinforcement-learning version (WZCQ) by the same author.

Use cases

• train an AI to play Honor of Kings from screen captures
• learn how to combine ResNet and GPT for game-playing agents
• collect training data from Android gameplay via scrcpy and minitouch
• experiment with imitation learning on mobile game footage
• study a reinforcement learning replacement for a behavior-cloned game AI

When to choose

• you want a hands-on example of vision-based game AI in PyTorch
• you need a reference for capturing Android game screens and injecting touch input
• you are learning how ResNet encoders and Transformer decoders fit together for sequential decision-making

When to avoid

• you need a production-ready or actively maintained game bot
• your device runs Android 10 or later (minitouch is unsupported)
• you expect competitive-level play - the model was trained on only ~100 matches and performs poorly
• you need a permissively licensed codebase - the project has no license

Facets

learning-resource · maturity abandoned

machine-learning deep-learning computer-vision reinforcement-learning image-processing machine-learning deep-learning gaming-tools computer-vision reinforcement-learning windows python game-ai honor-of-kings resnet gpt pytorch behavioral-cloning scrcpy minitouch imitation-learning android

Member repositories

For agents

markdown · JSON · MCP: product_card(name="FengQuanLi/WZCQ")