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SAC algorithm (#282)

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* 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
This commit is contained in:
guyk1971
2019-05-01 18:37:49 +03:00
committed by shadiendrawis
parent 33dc29ee99
commit 74db141d5e
92 changed files with 2812 additions and 402 deletions
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docs/usage.html
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@@ -278,7 +278,8 @@ To do so, you should select an environment type and level through the command li
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<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">coach</span> <span class="o">-</span><span class="n">p</span> <span class="n">Doom_Basic_BC</span> <span class="o">-</span><span class="n">cp</span><span class="o">=</span><span class="s1">&#39;agent.load_memory_from_file_path=</span><span class="se">\&quot;</span><span class="s1">&lt;experiment dir&gt;/replay_buffer.p</span><span class="se">\&quot;</span><span class="s1">&#39;</span>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">rl_coach.core_types</span> <span class="kn">import</span> <span class="n">PickledReplayBuffer</span>
<span class="n">coach</span> <span class="o">-</span><span class="n">p</span> <span class="n">Doom_Basic_BC</span> <span class="o">-</span><span class="n">cp</span><span class="o">=</span><span class="s1">&#39;agent.load_memory_from_file_path=PickledReplayBuffer(</span><span class="se">\&quot;</span><span class="s1">&lt;experiment dir&gt;/replay_buffer.p</span><span class="se">\&quot;</span><span class="s1">&#39;</span><span class="p">)</span>
</pre></div>
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