There are 7 repositories under c51 topic.
Clean, Robust, and Unified PyTorch implementation of popular Deep Reinforcement Learning (DRL) algorithms (Q-learning, Duel DDQN, PER, C51, Noisy DQN, PPO, DDPG, TD3, SAC, ASL)
An embedded development environment for mcs51/stm8/avr/cortex-m/riscv on VsCode.
Master classic RL, deep RL, distributional RL, inverse RL, and more using OpenAI Gym and TensorFlow with extensive Math
A pytorch tutorial for DRL(Deep Reinforcement Learning)
Deep Reinforcement Learning codes for study. Currently, there are only codes for algorithms: DQN, C51, QR-DQN, IQN, QUOTA.
C51-DDQN in Keras
DQN-Atari-Agents: Modularized & Parallel PyTorch implementation of several DQN Agents, i.a. DDQN, Dueling DQN, Noisy DQN, C51, Rainbow, and DRQN
A collection of Deep Reinforcement Learning algorithms implemented with PyTorch to solve Atari games and classic control tasks like CartPole, LunarLander, and MountainCar.
Paddle-RLBooks is a reinforcement learning code study guide based on pure PaddlePaddle.
🐳 Implementation of various Distributional Reinforcement Learning Algorithms using TensorFlow2.
An implementation of an Autonomous Vehicle Agent in CARLA simulator, using TF-Agents
Implementation of some of the Deep Distributional Reinforcement Learning Algorithms.
PyTorch - Implicit Quantile Networks - Quantile Regression - C51
A STCmicro STC15W4K32S4 series micro controller turns an IBM Wheelwriter Electronic Typewriter into a teletype-like device.
A Dallas Semiconductor DS89C440 MCU turns an IBM Wheelwriter Electronic typewriter into a Windows "Generic/Text Only" Printer.
A TF2.0 implementation of RL baselines.
Anhui Agriculture University C51 MCU Homework |安徽农业大学单片机接口与技术综合实践作业
Naive implementations of deep reinforcement learning algorithms
一种有限状态机(Mealy)的精简实现,编码遵循 ANSI C,易于扩展和学习,非常适用于资源有限的场景。 其工作过程如下: 1、使用指定起始状态和最终状态初始化状态机,并设置状态机的当前状态为起始状态。状态机开始工作。 2、在相关事件发生时,把事件关联的变量值传递给状态机并执行状态转换活动。 3、如果状态机进入最终状态(使用当前状态是否等于最终状态来判断),则状态机停机;否则继续工作。
A music alarm clock based on a 51 single -chip machine.