# Running rfgb¶

Object and their relationships are a natural way to think about the world. In this example, we have some facts about the world which we want to learn from. More specifically, we have a table of people and their relationships.

 Name Gender Child Sibling James Male [Harry] Lily Female [Harry] Petunia Harry Male Arthur Male [Ron, Fred] Molly Female [Ron, Fred] Ron Male [Fred] Fred Male [Ron]

Assume that the goal is to learn father(Y,X). We want to learn logical rules representing that domain object X is the father of Y (both of which are people in this case), given that you know information about their gender, children, and siblings.

## From Tables to First-order Predicate Logic¶

Once we have a high-level idea of what these relationships look like, the next step is to convert this into predicate logic format. This format is standard for most Prolog-based systems.

A few assumptions we will make about our data:

1. ‘Name’ is an identifier.
2. ‘Gender’ is male or female in this case, so we can make it a true/false value.
3. ‘Child’ and ‘Sibling’ are binary relationships encoding a relationship between two people (e.g. childof(lily, harry) denotes that ‘harry’ is the childof ‘lily’).

The target we want to learn is father(x,y). To learn this rule, rfgb learns a decision tree that most effectively splits the positive and negative examples. This example is fairly small so a small number of trees should suffice, but for more complicated problem more may be needed to learn a robust model.

Positive Examples:

father(harrypotter,jamespotter).
father(ginnyweasley,arthurweasley).
father(ronweasley,arthurweasley).
father(fredweasley,arthurweasley).
...


Negative Examples:

father(harrypotter,mollyweasley).
father(georgeweasley,jamespotter).
father(harrypotter,arthurweasley).
father(harrypotter,lilypotter).
father(ginnyweasley,harrypotter).
father(mollyweasley,arthurweasley).
father(fredweasley,georgeweasley).
father(georgeweasley,fredweasley).
father(harrypotter,ronweasley).
father(georgeweasley,harrypotter).
father(mollyweasley,lilypotter).
...


Facts:

male(jamespotter).
male(harrypotter).
male(arthurweasley).
male(ronweasley).
male(fredweasley).
male(georgeweasley).
siblingof(ronweasley,fredweasley).
siblingof(ronweasley,georgeweasley).
siblingof(ronweasley,ginnyweasley).
siblingof(fredweasley,ronweasley).
siblingof(fredweasley,georgeweasley).
siblingof(fredweasley,ginnyweasley).
siblingof(georgeweasley,ronweasley).
siblingof(georgeweasley,fredweasley).
siblingof(georgeweasley,ginnyweasley).
siblingof(ginnyweasley,ronweasley).
siblingof(ginnyweasley,fredweasley).
siblingof(ginnyweasley,georgeweasley).
childof(jamespotter,harrypotter).
childof(lilypotter,harrypotter).
childof(arthurweasley,ronweasley).
childof(mollyweasley,ronweasley).
childof(arthurweasley,fredweasley).
childof(mollyweasley,fredweasley).
childof(arthurweasley,georgeweasley).
childof(mollyweasley,georgeweasley).
childof(arthurweasley,ginnyweasley).
childof(mollyweasley,ginnyweasley).
...


## Training a Model¶

There is one more piece we still need: background knowledge about the world.

// Parameters
setParam: maxTreeDepth=3.
setParam: nodeSize=1.
setParam: numOfClauses=8.

// Modes
mode: male(+name).
mode: childof(+name,+name).
mode: siblingof(+name,-name).
mode: father(+name,+name).


Begin training:

python -m rfgb --help