A Knowledge Compilation Map

TL;DR

This paper introduces a framework for analyzing knowledge compilation approaches based on succinctness and query support, and presents a comprehensive map including classical and nested languages like OBDDs.

Contribution

It provides a systematic analysis and classification of knowledge compilation languages along key dimensions, extending beyond traditional flat languages to include nested structures.

Findings

The knowledge compilation map categorizes many existing languages.

Nested languages like OBDDs are shown to encompass many target languages.

Analysis helps position new approaches within the existing landscape.

Abstract

We propose a perspective on knowledge compilation which calls for analyzing different compilation approaches according to two key dimensions: the succinctness of the target compilation language, and the class of queries and transformations that the language supports in polytime. We then provide a knowledge compilation map, which analyzes a large number of existing target compilation languages according to their succinctness and their polytime transformations and queries. We argue that such analysis is necessary for placing new compilation approaches within the context of existing ones. We also go beyond classical, flat target compilation languages based on CNF and DNF, and consider a richer, nested class based on directed acyclic graphs (such as OBDDs), which we show to include a relatively large number of target compilation languages.