RAPS: a rule-based language for specifying resource allocation and time-tabling problems

Abstract

A general language for specifying resource allocation and time-tabling problems is presented. The language is based on an expert system paradigm that was developed previously by the authors and that enables the solution of resource allocation problems by using experts' knowledge and heuristics. The language enables the specification of a problem in terms of resources, activities, allocation rules, and constraints, and thus provides a convenient knowledge acquisition tool. The language syntax is powerful and allows the specification of rules and constraints that are very difficult to formulate with traditional approaches, and it also supports the specification of various control and backtracking strategies. We constructed a generalized inference engine that runs compiled resource allocation problem specification language (RAPS) programs and provides all necessary control structures. This engine acts as an expert system shell and is called expert system for resource allocation (ESRA). The performance of RAPS combined with ESRA is demonstrated by analyzing its solution of a typical resource allocation problem.

Model-based control architecture for attentive robots in rescue scenarios

“…This approach is similar to the one in Williams et al (2004), Simmons and Apfelbaum (1998), Solotorevsky et al (1994).…”

Parallelizing a CLIPS-based course timetabling expert system

“…Separating out the data, the knowledge, and the algorithms provides the flexibility to deal with changes, and the incorporation of human expertise helps to reduce the feasible solution search space. Solotorevsky, Gudes, and Meisels (1994) develop a rule-based language, called RAPS, for specifying resource allocation problems and timetabling problems. The language enables the specification of a problem in terms of resources, activities, allocation rules, and constraints, and thereby provides a convenient knowledge acquisition tool.…”