-
Deep-Reinforcement-Learning-Algorithms
32 projects in the framework of Deep Reinforcement Learning algorithms: Q-learning, DQN, PPO, DDPG, TD3, SAC, A2C and others. Each project is provided with a detailed training log.
-
InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
It can be solved in 113 episodes by Hill Climbing algorithm, https://github.com/Rafael1s/Deep-Reinforcement-Learning-Algorithms/tree/master/CartPole-Policy-Based-Hill-Climbingor by Double Deep Q-Learning in 612 episodes, https://github.com/Rafael1s/Deep-Reinforcement-Learning-Algorithms/tree/master/Cartpole-Double-Deep-Q-Learning
NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a more popular project.
Related posts
-
Is there a canonical simple "helloworld" neural network design? Something beyond AND/OR logic, a handful of nodes that does something mildly "useful"?
-
Need help with PyTorch script for Actor_Critic implementation of MountainCar env.
-
Is it better to not use the Target Update Frequency in Double DQN or depends on the application?
-
Working with DQN ! need some help !
-
他們能回來嗎