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Interpretation as Abduction
, 1990
"... An approach to abductive inference developed in the TACITUS project has resulted in a dramatic simplification of how the problem of interpreting texts is conceptualized. Its use in solving the local pragmatics problems of reference, compound nominals, syntactic ambiguity, and metonymy is described ..."
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Cited by 687 (38 self)
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An approach to abductive inference developed in the TACITUS project has resulted in a dramatic simplification of how the problem of interpreting texts is conceptualized. Its use in solving the local pragmatics problems of reference, compound nominals, syntactic ambiguity, and metonymy is described and illustrated. It also suggests an elegant and thorough integration of syntax, semantics, and pragmatics. 1
Semantics of paragraphs
- Computational Linguistics
, 1991
"... We present a computational theory of the paragraph. Within it we formally define coherence, give semantics to the adversative conjunction "but " and to the Gricean maxim of quantity, and present some new methods for anaphora resolution. The theory precisely characterizes the relati ..."
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Cited by 19 (3 self)
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We present a computational theory of the paragraph. Within it we formally define coherence, give semantics to the adversative conjunction "but " and to the Gricean maxim of quantity, and present some new methods for anaphora resolution. The theory precisely characterizes the relationship between the content of the paragraph and background knowledge needed for its understanding. This is achieved by introducing a new type of logical theory consisting of an object level, corresponding to the content of the paragraph, a referential level, which is a new logical level encoding background knowledge, and a metalevel containing constraints on models of discourse (e.g. a formal version of Gricean maxims). We propose also specific mechanisms of interaction between these levels, resembling both classical provability and abduction. Paragraphs are then represented by a class of structures called p-models. 1.
The (Extensive) Implications of Evaluation on the Development of Knowledge-Based System
- In Proceedings of the 9th AAAI-Sponsored Banff Knowledge Acquisition for Knowledge Based Systems
, 1995
"... : We argue that adding a requirement of evaluation and testing fundamentally changes KBS practice. In particular: (i) a fundamental change to the symbol-level representation in KBS; (ii) a rejection of certain unnecessary knowledge-level distinctions; (iii) a fundamental change to the inference engi ..."
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Cited by 14 (11 self)
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: We argue that adding a requirement of evaluation and testing fundamentally changes KBS practice. In particular: (i) a fundamental change to the symbol-level representation in KBS; (ii) a rejection of certain unnecessary knowledge-level distinctions; (iii) a fundamental change to the inference engine of KBS; and (iv) a basic computational limit to the size and internal complexity of the models we create via knowledge acquisition. 1. INTRODUCTION It would be convenient if KBS evaluation was neutral with respect to KBS practice. If an evaluation module was merely a post-hoc bolt-on, then its design could be deferred until after a system was developed. However, if evaluation adds extra requirements and restrictions to the KBS process, then the design of an evaluation module must be integrated with the system it will test. This paper argues for the inconvenient latter position. Models constructed in vague domains (defined below) are possibly inaccurate. Possibly inaccurate models must b...
Ripple-Down Rationality: A Framework for Maintaining PSMs
- In Workshop on Problem-Solving Methods for Knowledge-based Systems, IJCAI '97
, 1997
"... Knowledge-level (KL) modeling can be characterised as theory subset extraction where the extracted subset is consistent and relevant to some problem. Theory subset extraction is a synonym for Newell's principle of rationality, Clancey's model construction operators, and Breuker's comp ..."
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Cited by 9 (8 self)
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Knowledge-level (KL) modeling can be characterised as theory subset extraction where the extracted subset is consistent and relevant to some problem. Theory subset extraction is a synonym for Newell's principle of rationality, Clancey's model construction operators, and Breuker's components of expert solutions. In an abductive framework, a PSM is the extraction controller and is represented by a suite of BEST inference assessment operators. Each BEST operator is a single-classification expert system which accepts or culls a possible inference. PSMs can therefore be maintained by rippledown -rules, a technique for maintaining singleclassification expert systems. 1 Introduction Newell's knowledge-level (KL) approach modeled intelligence [37] as a search for appropriate operators that convert some current state to a goal state. Domain-specific knowledge are used to select the operators according to the principle of rationality; i.e. an intelligent agent will select an operator which i...
On the Value of Stochastic Abduction (if you fix everything, you loss fixes for everything else)
"... Back in the 1980s, the model-based diagnosis (MBD) community explored qualitative representations [42]. Since they are not overly-specific, such representations can be quickly collected in a new domain. Indeed, in domains where information is limited, ..."
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Cited by 7 (7 self)
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Back in the 1980s, the model-based diagnosis (MBD) community explored qualitative representations [42]. Since they are not overly-specific, such representations can be quickly collected in a new domain. Indeed, in domains where information is limited,
Exhaustive Abduction: A Practical Model Validation Tool
- In ECAI '94 Workshop on Validation of Knowledge-Based Systems
, 1994
"... Models should be able to reproduce the known behaviour of whatever it is they are trying to model. In its most general form, this test is abduction; i.e. the generating an internally-consistent scenario that entails some subset of known observations given certain inputs. Exhaustive abduction (EA) is ..."
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Cited by 6 (5 self)
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Models should be able to reproduce the known behaviour of whatever it is they are trying to model. In its most general form, this test is abduction; i.e. the generating an internally-consistent scenario that entails some subset of known observations given certain inputs. Exhaustive abduction (EA) is the generation of all such scenarios. EA can be used to verify a model. If all of the known behaviour cannot be found in any of the generated scenarios, then the model must be faulty. Given that abduction is known to be slow, a reasonable preexperimental intuition is that EA would not be a practical technique for large models. In the study presented here, EAs were executed for a variety of models of different sizes and internal fan-outs. The limits of EA for the current implementation and the studied models implied that EA has some practical utility as a validation tool. Keywords: validation, abduction, hypothesis testing, qualitative reasoning, neuroendocrinology. 1. INTRODUCTION Models...
A Precise Semantics For Vague Diagrams
, 1994
"... Informal vague causal diagrams (VCDs) are a common technique for illustrating and sharing expert intuitions. Normally, VCDs are viewed as precursors to other modelling techniques which necessitates further knowledge acquisition. Here we explore what semantics can be granted to VCDs, without having t ..."
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Cited by 2 (2 self)
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Informal vague causal diagrams (VCDs) are a common technique for illustrating and sharing expert intuitions. Normally, VCDs are viewed as precursors to other modelling techniques which necessitates further knowledge acquisition. Here we explore what semantics can be granted to VCDs, without having to request more information from the expert(s) or the domain. The impreciseness of VCDs typically makes them indeterminate. VCD inferencing must assume multiple possibilities and manage mutually exclusive possibilities in separate worlds. Given a library of known behaviour of the entity being modelled, we can use exhaustive abduction over VCDs to prove what behaviours are categorically impossible; i.e. we can use VCDs for knowledge acquisition.
Appropriate Responses to the Challenge of Situated Cognition for Knowledge Acquisition
, 1996
"... The dominant knowledge modeling paradigm in the KA field assumes that old knowledge expressed symbolically (i.e. problem-solving strategies or ontologies) is a productivity tool for building new knowledge bases. That is, it assumes that knowledge is context-independent. Researchers of situated cogni ..."
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Cited by 1 (1 self)
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The dominant knowledge modeling paradigm in the KA field assumes that old knowledge expressed symbolically (i.e. problem-solving strategies or ontologies) is a productivity tool for building new knowledge bases. That is, it assumes that knowledge is context-independent. Researchers of situated cognition (SC) claims that knowledge is mostly context-dependent and that concepts elicited prior to direct experience are less important than functional units developed via direct experience with the current problem. We argue that there is sufficient evidence to support some of the SC view; i.e. we may need to modify the knowledge modeling approach. Symbolic approaches exist which could be said to handle SC; e.g. abduction, verification & validation tools, repitory grids, certain frameworks for decision support systems, expert critiquing systems, ripple-down-rules, and rippledown -models. However, such approaches need careful assessment in order to test their appropriateness as a response to the...
Vague Models and Their Implications for the KBS Design Cycle
, 1996
"... Standard software engineering methodologies are typically prescriptions on how to develop some initial system. Here we formalise the process of using an existing, possibly poorly understood, system. Informal vague causal diagrams are a common technique for illustrating and sharing intuitions about s ..."
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Cited by 1 (1 self)
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Standard software engineering methodologies are typically prescriptions on how to develop some initial system. Here we formalise the process of using an existing, possibly poorly understood, system. Informal vague causal diagrams are a common technique for illustrating and sharing intuitions about such poorly understood systems. Normally, such diagrams are viewed as precursors to other modeling techniques. Here, we take another approach and explore what we can do with these vague diagrams without requiring precise analysis. Vague models can contain inaccuracies and must be tested. In vague domains, if we can't test it then we shouldn't model it. That is, the computational properties of the test engine constrains the modeling process 1 Introduction Informal vague causal diagrams such as Figure 1 are a common technique for illustrating and sharing intuitions about a domain. Normally, such diagrams are viewed as precursors to other modeling techniques. That is, the standard approach is ...
