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An implementation of the Deep Deterministic Policy Gradient (DDPG) algorithm using Keras/Tensorflow with the robot simulated using ROS/Gazebo/MoveIt!
Hi,
Thank you for publishing this project.
I'm a ROS newbie. Could you include a launch file to run this project ?
Or any other command.
Thank you very much,
Regards,
Marcos
I've executed your code....
with this change (because of the error...)
<<< in Actor and Critic Net. >>>
V = Dense(action_dim, init=lambda shape, name: uniform(shape, scale=3e-3, name=name),activation='linear')(h3)
----> V = Dense(action_dim, init = 'uniform', activation='linear')(h3)
error was this: TypeError: () takes exactly 2 arguments (1 given)
After modifying the code,,, It does not converge at all.........
is it because of the change>???
In Actor and Critic Networks python code,
I got this error with this code part
V = Dense(action_dim,init=lambda shape, name: uniform(shape, scale=3e-3, name=name),activation='linear')(h3)
TypeError: () takes exactly 2 arguments (1 given)
.... Could you give me solution... please???
I have implemented DDPG with ur_gazebo(ur3) and it worked but,,, it takes too much time to converge... So I want to refer your implementation..
If you want, I can share my implementation.
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