title: How to limit the actor outputs in a specific range?
body: <p>I'm trying to apply deep-deterministic-policy-gradient (DDPG) on a process control problem. The action outputs are continuous. For example, the temperature of the process would be 25 to 100 degree C, or the motor spin rate would be 0 to 3.0 rpm. The purpose of my work is to improve the product quality of that process by applying the best action outputs to that process. I think Actor-Critic and DDPG algorithm will be a good approach to my problem.</p>
  
  <p>When I was implementing the Actor part, I found most of the examples online limited the Actor outputs in the range of (-1, 1). This is, a tanh activation function.</p>
  
  <pre><code>import tensorflow as tf
  
  def actor_network(state):
      net = tf.layers.dense(state, 100, activation=tf.nn.relu)
      action = tf.layers.dense(net, action_dimension, activation=tf.nn.tanh)
      return action
  </code></pre>
  
  <p>Here's my question:</p>
  
  <p>How should I revise my actor network to limited the action outputs in the range of (25, 100) for temperature, and (0, 3.0) for motor spin rate?</p>