Conditional probability tables for Bayesian belief networks

A user interface for users of a belief network including a child node Y and one or more parent nodes Xi (i=1, . . . , n) for the child node Y,

• wherein the user interface is configured to display the child node Y, the parent nodes Xi, and one or more links that indicate relationships between the child node Y and the parent nodes Xi;
• and
• wherein the user interface is configured to allow the users of the belief network to indicate a desired strength of relationships between the child node Y and the parent nodes Xi by adjusting corresponding values on the links between the child node Y and the parent nodes Xi.

A method of computing a belief in a belief network including a child node Y and one or more parent nodes Xi (i=1, . . . , n) for the child node Y, the method comprising:

• receiving as input one or more parameters of a causal influence model that describes influence of the parent nodes Xi on possible states of the child node Y;
• and
• converting the parameters of the causal influence model into one or more entries of a conditional probability table that provides a probability distribution for all the possible states of the child node Y, for each combination of possible states of the parent nodes Xi.

A computer-readable medium having stored therein computer-usable instructions for a processing system, wherein said instructions when executed by the processing system causes the processing system to:

• receive as input one or more parameters of a causal influence model that describes influence of one or more parent nodes Xi (i=1, . . . , n) in a belief network on possible states of a child node Y in the belief network;
• and
• convert the parameters of the causal influence model into one or more entries of a conditional probability table that provides a probability distribution for all the possible states of the child node Y, for each combination of possible states of the parent nodes Xi(i=1, . . . , n).