RULEMASTER: A second-generation knowledge-engineering facility

Simulation and expert systems are remarkably similar. Both employ various representations to model some aspect of an uncertain world, with the model being formed as a piece of com puter software. This is then employed to aid decision making. Ideas about combining simulation and expert systems are presented, and a taxonomy is developed. It is concluded that the most fruitful areas of cross-fertilization are advice-giving ex pert systems that assist the simulation scientist and simulation user, new simulation tools built from knowledge-based tools, and intelligent front ends for simulation packages. Advice-giving systems will increasingly be part of simulation environments, rather than stand alone.