People have many constraints concerning the food they eat. These constraints
can be based on religious believes, be due to food allergies or to illnesses, or can
be derived just from personal preferences. Therefore, preparing menus at hospitals
and restaurants can be really complex. Another special situation arise when travel-
ing abroad. It is not always enough to know the brief description in the restaurant
menu or the explanation of the waiter. For example, “calamares en su tinta” (squid
in its own ink) is a delicious typical Spanish dish, not well-known abroad. Its brief
description would be “squid with boiled rice in its own (black) ink”. But an in-
gredient (included in a small amount, in order to thicken the sauce) is flour, a fact
very important for someone suffering from celiac disease. Therefore, we have con-
sidered that it would be very interesting to develop a Rule Based Expert System
(RBES) to address these problems. The rules derive directly from the recipes and
contain the information about required ingredients and names of the dishes. We
distinguish: ingredients and ways of cooking, intermediate products (like “mayon-
naise”, that doesn’t always appear explicitly in the restaurants’ menus) and final
products (like “seafood cocktail”, that are the dishes listed in the restaurant menu).
For each customer at a certain moment, the input to the system are: on one hand,
the stock of ingredients at that moment, and on the other, the religion, allergies and
restrictions due to illnesses or personal preferences of the customer. The RBES
then constructs a “personalized restaurant menu” using set operations and knowl-
edge extraction (thanks to an algebraic Groebner bases-based inference engine[1]).
The RBES has been implemented in the computer algebra system
Maple TM 18(us-ing its convenient Embedded Components) and can be run from computers and tablets using Maple TM or the Maple TM Player
