Add prior-sample and rejection-sampling markdowns.

Additional, minor layout tidy up in elimination-ask.

Author: ctjoreilly

README.md

@@ -222,6 +222,16 @@ The file [aima3e-algorithms.pdf](https://github.com/aimacode/pseudocode/blob/mas
        <td align="center"></td>
        <td><a href="md/Elimination-Ask.md">ELIMINATION-ASK</a></td>
    </tr>
+   <tr>
+       <td align="center">&bull;</td>
+       <td align="center"></td>
+       <td><a href="md/Prior-Sample.md">PRIOR-SAMPLE</a></td>
+   </tr>
+   <tr>
+       <td align="center">&bull;</td>
+       <td align="center"></td>
+       <td><a href=md/Rejection-Sampling.md"">REJECTION-SAMPLING</a></td>
+   </tr>
    <tr>
        <td align="center">&bull;</td>
        <td align="center"></td>

md/Elimination-Ask.md

@@ -10,7 +10,7 @@ __function__ ELIMINATION-ASK(_X_, __e__, _bn_) __returns__ a distribution over _
  __for each__ _var_ __in__ ORDER(_bn_.VARS) __do__  
    _factors_ ← \[MAKE\-FACTOR(_var_, __e__) | _factors_\]  
    __if__ _var_ is a hidden variable __then__ _factors_ ← SUM\-OUT(_var_, _factors_)  
-__return__ NORMALIZE(POINTWISE\-PRODUCT(_factors_))  
+ __return__ NORMALIZE(POINTWISE\-PRODUCT(_factors_))  
 
 ---
 __Figure__ ?? The variable elimination algorithm for inference in Bayesian networks.

md/Prior-Sample.md

@@ -0,0 +1,13 @@
+# PRIOR-SAMPLE
+
+## AIMA3e
+__function__ PRIOR-SAMPLE(_bn_) __returns__ an event sampled from the prior specified by _bn_  
+&emsp;__inputs__: _bn_, a Bayesian network specifying joint distribution __P__(_X<sub>1</sub>_, &hellip;, _X<sub>n</sub>_)  
+
+&emsp;__x__ &larr; an event with _n_ elements  
+&emsp;__foreach__ varaible _X<sub>i</sub>_ __in__ _X<sub>1</sub>_, &hellip;, _X<sub>n</sub>_ __do__  
+&emsp;&emsp;&emsp;_x_\[_i_\] &larr; a random sample from __P__(_X<sub>i</sub>_ &vert; _parents_(_X<sub>i</sub>_))  
+&emsp;__return x__
+
+---
+__Figure__ ?? A sampling algorithm that generates events from a Bayesian network. Each variable is sampled according to the conditional distribution given the values already sampled for the variable's parents.

md/Rejection-Sampling.md

@@ -0,0 +1,18 @@
+# REJECTION-SAMPLING
+
+## AIMA3e
+__function__ REJECTION-SAMPLING(_X_, __e__, _bn_, _N_) __returns__ an estimate of __P__(_X_ | __e__)  
+ __inputs__: _X_, the query variable  
+     __e__, observed values for variables __E__  
+     _bn_, a Bayesian network  
+     _N_, the total number of samples to be generated  
+ __local variables__: __N__, a vector of counts for each value of _X_, initially zero  
+
+ __for__ _j_ = 1 to _N_ __do__  
+   __x__ ← PRIOR\-SAMPLE(_bn_)  
+   __if x__ is consistent with __e then__  
+     __N__\[_x_\] ← __N__\[_x_\] + 1 where _x_ is the value of _X_ in __x__  
+ __return__ NORMALIZE(__N__)  
+
+---
+__Figure__ ?? The rejection\-sampling algorithm for answering queries given evidence in a Bayesian network.