The role of common sense knowledge in menu planning

摘要

Planning nutritious and appetizing menus is a task at which experts consistently outperform computer systems, making it a challenging domain for AI research. This paper describes lessons learned through the sequential construction of four expert systems for menu planning. The first of these systems, ESOMP (Expert System on Menu Planning), was built to plan menus for patients on severely restricted low protein diets. A need for common sense in structuring “sensible” looking meals was identified and addressed via meal patterns and food exchange groups. PRISM (Pattern Regulator for the Intelligent Selection of Menus) expanded upon ESOMP by planning menus to meet a broad range of dietary requirements and personal preferences. Simple knowledge representation structures, implemented in PRISM 1.0, proved inadequate for the expanded task. A hierarchical network structure was developed and implemented in PRISM 2.0 and PRISM 3.0. This structure captures the common sense concept of menu form and describes context-sensitive relationships among menu parts. A major contribution of this paper is showing how to represent common sense knowledge about food and menus in a form amenable to successful menu planning.