The Advantages of Explicitly Representing Problem Spaces

Abstract

Newell and Simon (1972) coined the term “problem space” for a virtual structure: all possible lines of reasoning that can be employed by an agent to solve a problem. For certain toy problems (e.g., Tower of Hanoi), the problem space can be represented explicitly as labeled, directed graph. For non-toy problems, cognitive scientists have sometimes employed the concept of a problem space to analyze tasks, but seem to feel that explicit representation of the whole problem space for a problem is probably not worthwhile, and perhaps not even feasible. I will present techniques developed over a decade of research that make explicit representation of large problem spaces feasible. I will demonstrate how explicit representations of problem spaces have been used in systems that do non-trivial user modeling, task analysis, intelligent tutoring, and natural language dialogues