posted on 2011-01-12, 09:17authored byJohn E. Heaton
The thesis describes a rational reconstruction of Sowa's theory of Conceptual
Graphs. The reconstruction produces a theory with a firmer logical foundation than was
previously the case and which is suitable for computation whilst retaining the
expressiveness of the original theory. Also, several areas of incompleteness are
addressed. These mainly concern the scope of operations on conceptual graphs of
different types but include extensions for logics of higher orders than first order. An
important innovation is the placing of negation onto a sound representational basis.
A comparison of theorem proving techniques is made from which the principles of
theorem proving in Peirce logic are identified. As a result, a set of derived inference rules,
suitable for a goal driven approach to theorem proving, is developed from Peirce's beta
rules. These derived rules, the first of their kind for Peirce logic and conceptual graphs,
allow the development of a novel theorem proving approach which has some similarities
to a combined semantic tableau and resolution methodology. With this methodology it is
shown that a logically complete yet tractable system is possible. An important result is the
identification of domain independent heuristics which follow directly from the
methodology. In addition to the theorem prover, an efficient system for the detection of
selectional constraint violations is developed.
The proof techniques are used to build a working knowledge base system in Prolog
which can accept arbitrary statements represented by conceptual graphs and test their
semantic and logical consistency against a dynamic knowledge base. The same proof
techniques are used to find solutions to arbitrary queries. Since the system is logically
complete it can maintain the integrity of its knowledge base and answer queries in a fully
automated manner. Thus the system is completely declarative and does not require any
programming whatever by a user with the result that all interaction with a user is
conversational. Finally, the system is compared with other theorem proving systems
which are based upon Conceptual Graphs and conclusions about the effectiveness of the
methodology are drawn.