A collection of Deep Reinforcement Learning algorithms implemented with PyTorch to solve Atari games and classic control tasks like CartPole, LunarLander, and MountainCar.

基于mapping.txt文件，根据原始class名或方法名获取混淆后的class名或方法名，根据混淆后的class名或方法名获取原始class名或方法名，堆栈还原等

Pytorch implementation of "Maximum a Posteriori Policy Optimization" with Retrace for Discrete gym environments

An Intellij IDEA and Android Studio Plugin to de-obfuscate your Proguard stack traces

Deep reinforcement learning framework for fast prototyping based on PyTorch

The Maze Solver program uses a backtracking algorithm to determine if a mouse can escape from a maze. It systematically tries all routes through the maze and retraces back its path when it reaches a dead end. If all routes are exhausted, the program determines that the mouse is trapped.