This thesis presents a case-based reasoning system (KICS) which can assist domain
experts in interpreting building regulations in relaxation cases. In traditional legal
decision support systems, it has been regarded as natural to represent legal rules in
statutes in terms of If-Then decision rules and to link these rules to a separate case-based
reasoning system for handling cases. However, we take a view that legal rules in
the statutory regulations are the results of accumulation and generalisation of rulings
made in case histories and this has led us to a unified case-based approach to handle
both statutory regulations and cases.
First, we propose a unified case-based model of regulatory information. In this model,
regulatory information, i.e., legal rules from statutes and precedent cases, are represented as models, and interpretation hierarchies of legal rules are represented as abstraction hierarchies of models in the Model Knowledge Base. Actual cases are stored
in the Case Library together with arguments debated. Background domain knowledge
used in classifying input cases are represented as semantic networks and heuristic rules
in the Domain Knowledge Base.
Second, we propose to use case-based reasoning to access and maintain regulatory
information. Models relevant to the input case are retrieved by identifying the level
of abstraction at which the input case is described and by selecting models similar to
the input case. If the input case is not compliant with the retrieved models, principles
behind retrieved legal rules and previous similar cases are explained to the user and
ask whether relaxation can be granted. Decision on relaxation is made by the user, and
rulings made in cases in which relaxation is granted are acquired by generalising them
and (if possible) combining them with existing models in the abstraction hierarchies.
Third, we describe the results of the evaluation of the prototype system carried out
using the Scottish building regulations and 22 appeals cases from the Building Direc¬
torate of The Scottish Office. The proposed framework has been successfully used to
process 22 appeal cases and has been demonstrated to be a flexible and efficient index¬
ing mechanism. The evaluation with real-world cases has also suggested that, as the
system moves towards the real-world environment, the retrieval algorithm needs to be
refined and supplied with more domain-specific knowledge.
The case-based approach proposed in this thesis provides a representational framework
in which legal rules at various abstraction levels including principles or legislative intentions can be explicitly represented and used to provide explanation. It also allows both
statutes and precedent cases to be integrated in one knowledge representation scheme.
Therefore, up-to-date interpretation of regulations can be maintained by accumulating
new rulings along with existing legal rules.