A generic ATMS

AbstractThe main aim of this paper is to create a general truth maintenance system based on the De Kleer algorithm. This system (the ATMS) is to be designed so that it can be used in different propositional monotonic logic models of reasoning systems. The knowledge base system that will interact with it is described. Furthermore, we study the efficiency that transferring the ATMS to a logic with several truth values presupposes. Definitions and properties of the generic ATMS are particularized to interact both with a reasoning system based on multivalued logic specifically for the case of [0, 1 ]-valued logic and with a reasoning system based on fuzzy logic. The latter will be designed to reason with fuzzy truth values, although a parallel project might be followed using linguistic labels directly

Plausible inference: A multi-valued logic for problem solving

A new logic is developed which permits continuously variable strength of belief in the truth of assertions. Four inference rules result, with formal logic as a limiting case. Quantification of belief is defined. Propagation of belief to linked assertions results from dependency-based techniques of truth maintenance so that local consistency is achieved or contradiction discovered in problem solving. Rules for combining, confirming, or disconfirming beliefs are given, and several heuristics are suggested that apply to revising already formed beliefs in the light of new evidence. The strength of belief that results in such revisions based on conflicting evidence are a highly subjective phenomenon. Certain quantification rules appear to reflect an orderliness in the subjectivity. Several examples of reasoning by plausible inference are given, including a legal example and one from robot learning. Propagation of belief takes place in directions forbidden in formal logic and this results in conclusions becoming possible for a given set of assertions that are not reachable by formal logic

Consistency reasoning in knowledge systems.

by Ying Kit Wong.Thesis (M.Phil.)--Chinese University of Hong Kong, 1997.Includes bibliographical references (leaves 144-146).AcknowledgmentsAbstractChapter 1 --- Introduction --- p.1Chapter 1.1 --- Characteristics of Human Commonsense Reasoning --- p.4Chapter 1.2 --- Neural-Logic Belief Network as the Basic Inconsistency Rea- soning System --- p.7Chapter 1.3 --- Consistency of Knowledge --- p.8Chapter 1.4 --- Update Sequence Independence in Belief States --- p.10Chapter 1.5 --- Lazy Consistency Reasoning --- p.12Chapter 1.6 --- Comparison of W-Consistency with Other Systems --- p.14Chapter 1.7 --- Integration of Different Methods in One Formalization --- p.16Chapter 2 --- Neural-Logic Belief Network (NLBN) --- p.17Chapter 2.1 --- Definitions --- p.17Chapter 2.2 --- Computation Functions --- p.20Chapter 3 --- W-Consistency Reasoning --- p.29Chapter 3.1 --- W-Consistency --- p.30Chapter 3.2 --- Logical Suppression --- p.33Chapter 3.3 --- Consistency Check --- p.35Chapter 3.4 --- Consistency Maintenance --- p.35Chapter 3.5 --- The W-Consistency Reasoning Process --- p.41Chapter 3.6 --- Proof of Consistency Reasoning Process Terminates Finitely and Consistent --- p.42Chapter 4 --- Implementation --- p.46Chapter 4.1 --- Introduction --- p.46Chapter 4.2 --- New Features in Phase Two --- p.48Chapter 4.2.1 --- Consistency Reasoning Function --- p.48Chapter 4.2.2 --- Knowledge File --- p.49Chapter 4.3 --- Inference Engine for Consistency Reasoning --- p.54Chapter 4.4 --- Examples of using XHOPES --- p.56Chapter 5 --- Comparison between NLBN with W-Consistency and AGM Logic --- p.63Chapter 5.1 --- AGM Logic with Epistemic Entrenchment --- p.64Chapter 5.1.1 --- Three Forms of Belief Change --- p.64Chapter 5.1.2 --- Epistemic Entrenchment --- p.67Chapter 5.2 --- Network Update Operators in NLBN vs. Belief Changesin AGM --- p.68Chapter 5.3 --- Epistemic Entrenchment vs. Degree-of-Belief --- p.77Chapter 5.4 --- Consistency Preservation --- p.80Chapter 5.5 --- Classical vs. Non-classical Logical Consistency --- p.82Chapter 5.6 --- Retraction vs. Suppression --- p.83Chapter 5.7 --- Foundation vs. Coherence Theories --- p.84Chapter 6 --- Comparison of W-Consistency with other Systems --- p.86Chapter 6.1 --- G-Consistency --- p.87Chapter 6.1.1 --- Overview of G-Consistency --- p.87Chapter 6.1.2 --- Comparison of W-Consistency with G-Consistency --- p.88Chapter 6.2 --- S-Consistency --- p.94Chapter 6.2.1 --- Overview of S-Consistency --- p.94Chapter 6.2.2 --- Comparison of W-Consistency with S-Consistency --- p.95Chapter 6.3 --- Truth Maintenance Systems --- p.97Chapter 6.3.1 --- Introduction of Truth Maintenance Systems --- p.97Chapter 6.3.2 --- Comparison of TMS between W-Consistency with NLBN --- p.99Chapter 7 --- Lazy Consistency Reasoning using W-Consistency --- p.102Chapter 7.1 --- Proof of Lazy Characteristic of W-Consistency --- p.104Chapter 7.2 --- Example of Lazy Consistency Reasoning --- p.112Chapter 7.3 --- Discussion and Application --- p.117Chapter 8 --- Integration of Different Consistency Reasoning Methods --- p.120Chapter 8.1 --- Mixing W-Consistency and G-Consistency into a NLBN --- p.121Chapter 8.2 --- Using a NLBN for Truth Maintenance --- p.129Chapter 8.2.1 --- TMS's Truth Maintenance Strategy --- p.129Chapter 8.2.2 --- Consistency Reasoning style of NLBN --- p.134Chapter 8.2.3 --- Using NLBN for TMS-style Truth Maintenance --- p.136Chapter 8.2.4 --- Discussion --- p.140Chapter 9 --- Conclusion --- p.143Chapter A --- Test Case for Merging Knowledge Bases Using XHOPES --- p.15

Mixed-initiative control of intelligent systems

Mixed-initiative user interfaces provide a means by which a human operator and an intelligent system may collectively share the task of deciding what to do next. Such interfaces are important to the effective utilization of real-time expert systems as assistants in the execution of critical tasks. Presented here is the Incremental Inference algorithm, a symbolic reasoning mechanism based on propositional logic and suited to the construction of mixed-initiative interfaces. The algorithm is similar in some respects to the Truth Maintenance System, but replaces the notion of 'justifications' with a notion of recency, allowing newer values to override older values yet permitting various interested parties to refresh these values as they become older and thus more vulnerable to change. A simple example is given of the use of the Incremental Inference algorithm plus an overview of the integration of this mechanism within the SPECTRUM expert system for geological interpretation of imaging spectrometer data

Extended incidence calculus and its comparison with related theories

This thesis presents a comprehensive study o f incidence calculus, a probabilistic logic for reasoning under uncertainty which extends two-value propositional logic to a multiple-value logic. There are three main contributions in this thesis.First of all, the original incidence calculus is extended considerably in three aspects: (a) the original incidence calculus is generalized; (b) an efficient algorithm for incidence assignment based on generalized incidence calculus is developed; (c) a combination rule is proposed for the combination of both independent and some dependent pieces of evidence. Extended incidence calculus has the advantages of representing information flexibly and combining multiple sources o f evidence.Secondly, a comprehensive comparison between extended incidence calculus and the Dempster-Shafer (DS) theory of evidence is provided. It is proved that extended incidence calculus is equivalent to DS theory in representing evidence and combining independent evidence but superior to DS theory in combining de­pendent evidence.Thirdly, the relations between extended incidence calculus and the assumption- based truth maintenance systems are discussed. It is proved that extended inci­dence calculus is equivalent to the ATM S in calculating labels for nodes. Extended incidence calculus can also be used as a basis for constructing probabilistic ATMSs.The study in this thesis reveals that extended incidence calculus can be re­garded as a bridge between numerical and symbolic reasoning mechanisms

Reason Maintenance - State of the Art

This paper describes state of the art in reason maintenance with a focus on its future usage in the KiWi project. To give a bigger picture of the field, it also mentions closely related issues such as non-monotonic logic and paraconsistency. The paper is organized as follows: first, two motivating scenarios referring to semantic wikis are presented which are then used to introduce the different reason maintenance techniques