There are many applications which may be done by an expert system in real time, if the system is capable of real time response. The Lisp and Prolog based expert systems have typically been too slow for real time response. This has lead to an effort to use other languages, the development of fast pattern matching techniques and other methods of improving the speed of expert systems. Another approach to developing faster expert systems is to make use of the emerging parallel processing computer technology. A further use for parallelism is to allow reasonable response time for large knowledge bases. The size of knowledge bases may become as large as 20,000 chunks of knowledge (and more) in the near future in medical and space applications. This paper describes the use of parallel processing in the EMYCIN backward chained rule-based model is used.
Lawrence O. Hall,
"Parallelism in backward-chained expert systems: experimental results", Proc. SPIE 1293, Applications of Artificial Intelligence VIII, (1 January 1990); doi: 10.1117/12.21137; https://doi.org/10.1117/12.21137