.. index:: Propagation

.. _Propagation:

Propagation
===========

Propagation describes the act of computing posterior probability distributions and expected utilities for unobserved :ref:`discrete chance nodes<discrete_chance_node>` and :ref:`decision nodes<decision_node>`, and distribution functions for :ref:`continuous chance nodes<continuous_chance_node>` given the values for the observed nodes (i.e., the evidence). 

Four different propagation algorithms are available: :ref:`Sum normal<prop_sum_normal>`, :ref:`max normal<prop_max_normal>`, :ref:`sum fast retraction<prop_sum_fast_retract>`, and :ref:`max fast retraction<prop_max_fast_retract>`. Each one of these can be activated by selecting the appropriate Propagate item of the :ref:`Network Menu<network_menu>`. In addition, two of the most common propagation algorithms (sum normal and max normal) can be accessed by pressing one of the propagation buttons of the :ref:`Run Mode<Run_mode>` Tool Bar (see Figure 1). If :ref:`auto propagation<auto_propagation>` has been specified, propagation will take place each time new evidence is entered.

.. figure:: images/propsumnormal.png

	Figure 1: The propagation button :ref:`sum normal<prop_sum_normal>` in the run mode toolbar or in th propagation menu in the network menu 