A knowledge-based system to represent spatial reasoning for fire modelling

This paper describes the architecture of the knowledge based system (KBS) component of Smartfire, a fire field modelling tool for use by members of the fire safety engineering community who are not expert in modelling techniques. The KBS captures the qualitative reasoning of an experienced modeller in the assessment of room geometries, so as to set up the important initial parameters of the problem. Fire modelling expertise is an example of geometric and spatial reasoning, which raises representational problems. The approach taken in this project is a qualitative representation of geometric room information based on Forbus’ concept of a metric diagram. This takes the form of a coarse grid, partitioning the domain in each of the three spatial dimensions. Inference over the representation is performed using a case-based reasoning (CBR) component. The CBR component stores example partitions with key set-up parameters; this paper concentrates on the key parameter of grid cell distribution.

A blackboard architecture for a hybrid CBR system for scientific software

This paper describes the use of a blackboard architecture for building a hybrid case based reasoning (CBR) system. The Smartfire fire field modelling package has been built using this architecture and includes a CBR component. It allows the integration into the system of qualitative spatial reasoning knowledge from domain experts. The system can be used for the automatic set-up of fire field models. This enables fire safety practitioners who are not expert in modelling techniques to use a fire modelling tool. The paper discusses the integrating powers of the architecture, which is based on a common knowledge representation comprising a metric diagram and place vocabulary and mechanisms for adaptation and conflict resolution built on the Blackboard.