2047708
Planning with Incomplete Information
Planning is a natural domain of application for frameworks of reasoning about actions and change. In this paper we study how one such framework, the Language E, can form the basis for planning under (possibly) incomplete information. We define two types of plans: weak and safe plans, and propose a planner, called the E-Planner, which is often able to extend an initial weak plan into a safe plan even though the (explicit) information available is incomplete, e.g. for cases where the initial state is not completely known. The E-Planner is based upon a reformulation of the Language E in argumentation terms and a natural proof theory resulting from the reformulation. It uses an extension of this proof theory by means of abduction for the generation of plans and adopts argumentation-based techniques for extending weak plans into safe plans. We provide representative examples illustrating the behaviour of the E-Planner, in particular for cases where the status of fluents is incompletely known.
991675
A Simple Declarative Language for Describing Narratives With Actions
Abstract We describe a simple declarative languageEfor describing the effects of a series of action occurrences within a narrative.Eis analogous to Gelfond and Lifschitz's LanguageAand its extensions, but is based on a different ontology. The semantics ofEis based on a simple characterisation of persistence which facilitates a modular approach to extending the expressivity of the language. Domain descriptions inAcan be translated to equivalent theories inE. We show how, in the context of reasoning about actions,E's narrative-based ontology may be exploited in order to characterise and synthesise two complementary notions of explanation. According to the first notion, explanation may be partly modelled as the process of suitably extending an apparently inconsistent theory written inEso as to establish consistency, thus providing a natural method, in many cases, to account for conflicting sets of information about the domain. According to the second notion, observations made at later times can sometimes be explained in terms of what is true at earlier times. This enables domains to be given an alternative characterisation in which knowledge arising from observations is appropriately separated from other aspects of the domain. We also describe howEdomains may be implemented as Event Calculus style logic programs, which facilitate automated reasoning both backwards and forwards in time, and which behave correctly even when the knowledge entailed by the domain description is incomplete.
10794263
E-RES: A System for Reasoning about Actions, Events and Observations
E-RES is a system that implements the Language E , a logic for reasoning about narratives of action occurrences and observations. E ’s semantics is modeltheoretic, but this implementation is based on a sound and complete reformulation of E in terms of argumentation, and uses general computational techniques of argumentation frameworks. The system derives sceptical non-monotonic consequences of a given reformulated theory which exactly correspond to consequences entailed by E ’s model-theory. The computation relies on a complimentary ability of the system to derive credulous non-monotonic consequences together with a set of supporting assumptions which is sufficient for the (credulous) conclusion to hold. E-RES allows theories to contain general action laws, statements about action occurrences, observations and statements of ramifications (or universal laws). It is able to derive consequences both forward and backward in time. This paper gives a short overview of the theoretical basis of E-RES and illustrates its use on a variety of examples. Currently, E-RES is being extended so that the system can be used for planning.
10913688
A Case Study in Reasoning about Actions and Continuous Change
This paper shows how the Situation Calculus can be extended to deal both with `narratives' and with domains containing real-valued parameters, whose actual values may vary continuously between the occurrences of actions. In particular, a domain is represented where action occurrences may be `triggered' at instants in time when certain parameters reach particular values. Its formalisation requires the integration of several types of default reasoning. Hence Baker's circumscriptive solution to the frame problem is extended to re ect the assumptions that by default a given action does not occur at a given time point, that by default a given set of parameter values does not trigger a given action, and that by default a given action occurrence does not result in a discontinuity for a given parameter. Regarding the minimisation of discontinuities, the example illustrates how circumstances can arise where, at a particular time point, discontinuities in some parameters can be `traded' for discontinuities in others. It is argued that, in general, in such cases extra domain-speci c information will be necessary in order to eliminate anomalous models of
12976067
Reasoning about Discontinuities in the Event Calculus
This paper describes a logic-based formalism which combines techniques for reasoning about actions with standard mathematical techniques for modelling dynamic systems using the diierential calculus. The formalism inherits a robust solution to the frame problem which can handle con-currency, non-determinism, domain constraints and narrative. It also incorporates a mechanism for reasoning about the boundary conditions associated with systems of diier-ential equations deened over various intervals. This mechanism overcomes a number of drawbacks of previous systems .
23103290
The Event Calculus in Classical Logic - Alternative Axiomatisations
5031776
The Automated Geospatial Watershed Assessment tool
A toolkit for distributed hydrologic modeling at multiple scales using two independent models within a geographic information system is presented. This open-source, freely available software was developed through a collaborative endeavor involving two Universities and two government agencies. Called the Automated Geospatial Watershed Assessment tool (AGWA), this software is written for the ArcView GIS platform and is distributed as an extension via the Internet. AGWA uses commonly available GIS data layers to fully parameterize, execute, and visualize results from both the Soil and Water Assessment Tool (SWAT) and Kinematic Runoff and Erosion model (KINEROS2). These two distributed hydrologic models operate at different time scales and are suitable for application across a range of spatial scales. Descriptions of the GIS framework, hydrologic models, spatial analyses and algorithms that control the modeling process are given. Model requirements, limitations on the model applications and calibration techniques are described with examples of the use of AGWA for watershed modeling and assessment at a range of scales. 2006 Elsevier Ltd. All rights reserved.
16826457
Creating Nested Mappings with Clio
Schema mappings play a central role in many data integration and data exchange scenarios. In those applications, users need to quickly and correctly specify how data represented in one format is converted into a different format. Clio (L. Popa et al., 2002) is a joint research project between IBM and the University of Toronto studying the creation, maintenance, and use of schema mappings. There have always been two goals in our work in Clio: 1) the automatic creation of logical assertions that capture the way one or more source schemas are mapped into a target schema, and 2) the generation of transformation queries or programs that transform a source data instance into a target data instance.
8719734
Association rules over interval data
We consider the problem of mining association rules over interval data (that is, ordered data for which the separation between data points has meaning). We show that the measures of what rules are most important (also called rule interest) that are used for mining nominal and ordinal data do not capture the semantics of interval data. In the presence of interval data, support and confidence are no longer intuitive measures of the interest of a rule. We propose a new definition of interest for association rules that takes into account the semantics of interval data. We developed an algorithm for mining association rules under the new definition and overview our experience using the algorithm on large real-life datasets.
1267904
Detecting Acromegaly: Screening for Disease with a Morphable Model
Acromegaly is a rare disorder which affects about 50 of every million people. The disease typically causes swelling of the hands, feet, and face, and eventually permanent changes to areas such as the jaw, brow ridge, and cheek bones. The disease is often missed by physicians and progresses beyond where it might if it were identified and treated earlier. We consider a semi-automated approach to detecting acromegaly, using a novel combination of support vector machines (SVMs) and a morphable model. Our training set consists of 24 frontal photographs of acromegalic patients and 25 of disease-free subjects. We modelled each subject's face in an analysis-by-synthesis loop using the three-dimensional morphable face model of Blanz and Vetter. The model parameters capture many features of the 3D shape of the subject's head from just a single photograph, and are used directly for classification. We report encouraging results of a classifier built from the training set of real human subjects.
4964831
Information-theoretic tools for mining database structure from large data sets
Data design has been characterized as a process of arriving at a design that maximizes the information content of each piece of data (or equivalently, one that minimizes redundancy). Information content (or redundancy) is measured with respect to a prescribed model for the data, a model that is often expressed as a set of constraints. In this work, we consider the problem of doing data redesign in an environment where the prescribed model is unknown or incomplete. Specifically, we consider the problem of finding structural clues in an instance of data, an instance which may contain errors, missing values, and duplicate records. We propose a set of information-theoretic tools for finding structural summaries that are useful in characterizing the information content of the data, and ultimately useful in data design. We provide algorithms for creating these summaries over large, categorical data sets. We study the use of these summaries in one specific physical design task, that of ranking functional dependencies based on their data redundancy. We show how our ranking can be used by a physical data-design tool to find good vertical decompositions of a relation (decompositions that improve the information content of the design). We present an evaluation of the approach on real data sets.