SAC algorithm (#282)

* SAC algorithm

* SAC - updates to agent (learn_from_batch), sac_head and sac_q_head to fix problem in gradient calculation. Now SAC agents is able to train.
gym_environment - fixing an error in access to gym.spaces

* Soft Actor Critic - code cleanup

* code cleanup

* V-head initialization fix

* SAC benchmarks

* SAC Documentation

* typo fix

* documentation fixes

* documentation and version update

* README typo

benchmarks/ddpg/README.md

@@ -1,6 +1,6 @@
 # DDPG
 
-Each experiment uses 3 seeds and is trained for 2k environment steps.
+Each experiment uses 3 seeds and is trained for 2M environment steps.
 The parameters used for DDPG are the same parameters as described in the [original paper](https://arxiv.org/abs/1509.02971).
 
 ### Inverted Pendulum DDPG - single worker