Truth maintenance in knowledge-based systems

Nguyen, Hai Hoang (2014) Truth maintenance in knowledge-based systems. PhD thesis, University of Nottingham.

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Truth Maintenance Systems (TMS) have been applied in a wide range of domains, from diagnosing electric circuits to belief revision in agent systems. There also has been work on using the TMS in modern Knowledge-Based Systems such as intelligent agents and ontologies. This thesis investigates the applications of TMSs in such systems.

For intelligent agents, we use a “light-weight” TMS to support query caching in agent programs. The TMS keeps track of the dependencies between a query and the facts used to derive it so that when the agent updates its database, only affected queries are invalidated and removed from the cache. The TMS employed here is “light-weight” as it does not maintain all intermediate reasoning results. Therefore, it is able to reduce memory consumption and to improve performance in a dynamic setting such as in multi-agent systems.

For ontologies, this work extends the Assumption-based Truth Maintenance System (ATMS) to tackle the problem of axiom pinpointing and debugging in ontology-based systems with different levels of expressivity. Starting with finding all errors in auto-generated ontology mappings using a “classic” ATMS [23], we extend the ATMS to solve the axiom pinpointing problem in Description Logics-based Ontologies. We also attempt this approach to solve the axiom pinpointing problem in a more expressive upper ontology, SUMO, whose underlying logic is undecidable.

Item Type: Thesis (University of Nottingham only) (PhD)
Supervisors: Alechina, Natasha
Logan, B.S.
Keywords: truth maintenance systems, knowledge-based systems, expert systems, computers, tms, assumption-based turth maintenance system
Subjects: Q Science > QA Mathematics > QA 75 Electronic computers. Computer science
Faculties/Schools: UK Campuses > Faculty of Science > School of Computer Science
Item ID: 28434
Depositing User: Jacob, Mr Tim
Date Deposited: 24 Feb 2015 14:15
Last Modified: 15 Dec 2017 11:55

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