•Assume variables are conditionally independent by default.
•Only represent direct causal links (conditional dependence)
between random variables.
•Belief network or
Bayesian network:
1.set
of random variables (nodes)
2.set
of directed links (edges) indicating direct influence of one variable on another.
3.a
table for each variable, supplying conditional probabilities of the variable for each assignment of its parents
4.no
directed cycles (network is a DAG)
