alex.ml.ep package

Submodules

alex.ml.ep.node module

class alex.ml.ep.node.ConstChangeGoal(name, desc, card, parameters, parents=None)[source]

Bases: alex.ml.ep.node.GroupingGoal

ConstChangeGoal implements all functionality as is include in GroupingGoal; however, it that there are only two transition probabilites for transitions between the same values and the different values.

update()[source]

This function update belief for the goal.

class alex.ml.ep.node.Goal(name, desc, card, parameters, parents=None)[source]

Bases: alex.ml.ep.node.Node

Goal can contain only the same values as the observations.

As a consequence, it can contain values of its previous node.

probTable(value, parents)[source]

This function defines how the coditional probability is computed.

pRemebering - probability that the previous value is correct pObserving - probability that the observed value is correct

setParents(parents)[source]
setValues()[source]

The function copy values from its previous node and from observation nodes.

update()[source]

This function update belief for the goal.

class alex.ml.ep.node.GroupingGoal(name, desc, card, parameters, parents=None)[source]

Bases: alex.ml.ep.node.GroupingNode, alex.ml.ep.node.Goal

GroupingGoal implements all functionality as is include in Goal; however, it only update the values for which was observed some evidence.

setValues()[source]

The function copy values from its previous node and from observation nodes.

update()[source]

This function update belief for the goal.

class alex.ml.ep.node.GroupingNode(name, desc, card)[source]

Bases: alex.ml.ep.node.Node

addOthers(value, probability)[source]
explain(full=None)[source]

This function explains the values for this node.

In additon to the Node’s function, it prints the cardinality of the others set.

splitOff(value)[source]

This function split off the value from the others set and place it into the values dict.

class alex.ml.ep.node.Node(name, desc, card)[source]

Bases: object

A base class for all nodes in a belief state.

explain(full=None)[source]

This function prints the values and their probailities for this node.

getMostProbableValue()[source]

The function returns the most probable value and its probability in a tuple.

getTwoMostProbableValues()[source]

This function returns two most probable values and their probabilities.

The function returns a tuple consisting of two tuples (value, probability).

normalise()[source]

This function normlize the sum of all probabilities to 1.0

alex.ml.ep.test module

alex.ml.ep.test.random() → x in the interval [0, 1).

alex.ml.ep.turn module

class alex.ml.ep.turn.Turn[source]

Module contents