the implement of REINFORCE algorithm and DDPG algorithm in pytorch
(update the implement in tensorflow v1 & v2)
(The convergence of tf version is quite slower than pytorch version, I don't know why, maybe the default initialization methods of these are different.)
all code is in one file and easily to follow
- tensorboardX (for logging, you can delete the logging code if you don't need)
- pytorch (>= 1.0, 1.0.1 used in my experiment)
- gym
only in CartPole-v0 environment, can not learn well in Pendulum-v0
only in Pendulum-v0 for ddpg only suit for continuous task
in pendulum-v0
TD-3 version with 2 critic networks and soft update, soft update version is the one in ddpg original paper, hard update version is the one with the same target network update with DQN which is every C time hard update.