Case-based design and learning in telecommunications
Costas Tsatsoulis · 1989
Design has been one of the most difficult problems that Artificial Intelligence has faced until now. Design knowledge is almost impossible to gather and put into rules or other structured reasoning tool, and studies of human expert designers have shown that often the design process seems ad hoc and based on “intuition”. This paper presents a novel approach to automating design by using case-based reasoning and learning. It discusses how cases of previous designs are stored, how they are retrieved, how they are judged based on their adherence to design specifications, how the designs are created, and how the memory of design cases is expanded by learning. Finally, this paper presents the current state of an automated design tool based on these principles, which will be used in the intelligent design of network topologies.