t">\(R(s)\)</span></p></li>
<li><p>find <span class="math notranslate nohighlight">\(U^\pi(s)\)</span> with the Bellman eqn (plug in at each step)</p></li>
<li><p>we might want to enforce a prior on the model (two ways)</p>
<ol class="arabic simple">
<li><p><em>Bayesian reinforcement learning</em> - assume a prior <span class="math notranslate nohighlight">\(P(h)\)</span> on transition model h</p></li>
</ol>
<ul class="simple">
<li><p>use prior to calculate <span class="math notranslate nohighlight">\(P(h \