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<div class="section" id="behavioral-cloning">
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<h1>Behavioral Cloning<a class="headerlink" href="#behavioral-cloning" title="Permalink to this headline">¶</a></h1>
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<p><strong>Actions space:</strong> Discrete | Continuous</p>
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<div class="section" id="network-structure">
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<h2>Network Structure<a class="headerlink" href="#network-structure" title="Permalink to this headline">¶</a></h2>
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<h2>Algorithm Description<a class="headerlink" href="#algorithm-description" title="Permalink to this headline">¶</a></h2>
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<h3>Training the network<a class="headerlink" href="#training-the-network" title="Permalink to this headline">¶</a></h3>
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<p>The replay buffer contains the expert demonstrations for the task.
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These demonstrations are given as state, action tuples, and with no reward.
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The training goal is to reduce the difference between the actions predicted by the network and the actions taken by
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the expert for each state.</p>
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<ol class="arabic simple">
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<li><p>Sample a batch of transitions from the replay buffer.</p></li>
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<li><p>Use the current states as input to the network, and the expert actions as the targets of the network.</p></li>
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<li><p>For the network head, we use the policy head, which uses the cross entropy loss function.</p></li>
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<dl class="class">
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<dt id="rl_coach.agents.bc_agent.BCAlgorithmParameters">
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<em class="property">class </em><code class="descclassname">rl_coach.agents.bc_agent.</code><code class="descname">BCAlgorithmParameters</code><a class="reference internal" href="../../../_modules/rl_coach/agents/bc_agent.html#BCAlgorithmParameters"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#rl_coach.agents.bc_agent.BCAlgorithmParameters" title="Permalink to this definition">¶</a></dt>
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