Rules Dependencies in Backward Chaining of Conceptual Graphs Rules

Abstract

Abstract. Conceptual Graphs Rules were proposed as an extension of Simple Conceptual Graphs (CGs) to represent knowledge of form "if A then B", where A and B are simple CGs. Optimizations of the deduction calculus in this KR formalism include a Backward Chaining that unifies at the same time whole subgraphs of a rule, and a Forward Chaining that relies on compiling dependencies between rules. In this paper, we show that the unification used in the first algorithm is exactly the operation required to compute dependencies in the second one. We also combine the benefits of the two approaches, by using the graph of rules dependencies in a Backward Chaining framework.

Formal Logic with Conceptual Graphs

“…Other approaches to employ reasoning facilities can be based on tableaux algorithms (see [Ker01] for an tableaux algorithm for CGs with full negation), or resolution-like calculi combined with projections [MS96,BS06].…”

Decision support for agri-food chains: A reverse engineering argumentation-based approach

“…Note that this technique is commonly used, for example, for backward chaining query answering (Baget and Salvat, 2006;Konig et al, 2012) where a query is rewritten according to the rules. The same mechanism is also discussed by abductive reasoning algorithms (Klarman et al, 2011) where minimal sets of facts (in the set inclusion sense) are added to the knowledge base in order to be able to deduct a query.…”

Information for decision-making is ubiquitous: Revisiting the reverse engineering mode in breadmaking technology

“…Note that this technique is commonly used, for example, for backward chaining query answering [33], [34] where a query is rewritten according to the rules. The same mechanism is also discussed by abductive reasoning algorithms [35] where minimal sets of facts (in the set inclusion sense) are added to the knowledge base in order to be able to deduct a query.…”