rvised learning</p></li>
</ul>
</li>
<li><p><em>Actor-critic</em>: estimate value function or Q-function of the current policy (critic), use it to improve policy (actor)</p></li>
<li><p><em>Model-based RL</em>: estimate the transition model, and then‚Ä¶</p>
<ul>
<li><p>just use the model to plan (no plicy)</p>
<ul>
<li><p>trajectory optimization/optimal control (continuous space) - optimize over actions</p></li>
<li><p>discrete planning - e.g. monte carlo tree search</p></li>
</ul>
</li>
<li><p>backprop