Split Up is an intelligent decision support system, which makes predictions about the distribution of marital property following divorce in Australia.
Split Up operates as a hybrid system, combining rule – based reasoning with neural network theory.
Split_up, with a view to overcome this flaw, uses argument structures proposed by Toulmin as the basis for representations from which explanations can be generated.
These needs can include factors such as the inability to gain employment, the continued care of a child under 18 years of age or medical expenses.
Split_up determines the percentage split by using a combination of rule- based reasoning and neural networks.
[2]: 196 In Split_Up, the neural network is a statistical technique for learning the weights of each of the relevant attributes used in a percentage split determination of marital property.
Hence the inputs to the neural network are contributions, future needs and wealth, and the output the percentage split predicted.
It is trained by repeatedly exposing it to examples of the problem and learning the significance (weights) of the input nodes.
[4]: 274 Since the manner in which these weights are learned is primarily statistical, domain knowledge of legal rules and principles is not modelled directly.