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LT revisited : explanation-based learning and the logic of Principia mathematica
This paper describes an explanation-based learning (EBL) system based on a version of Newell, Shaw and Simon's LOGIC-THEORIST (LT). Results of applying this system to propositional calculus problems from Principia Mathematica are compared with results of applying several other versions of the same performance element to these problems. The primary goal of this study is to characterize and analyze differences between not learning, rote learning (LT's original learning method), and EBL. Another aim is to provide base-line characterizations of the performance of a simple problem solver in the context of the Principa problems, in the hope that these problems can be used as a benchmark for testing improved learning methods, just as problems like chess and the eight puzzle have been used as benchmarks in research on search methods
Reason Maintenance - Conceptual Framework
This paper describes the conceptual framework for reason maintenance developed as part of
WP2
Focusing and Polarization in Intuitionistic Logic
A focused proof system provides a normal form to cut-free proofs that
structures the application of invertible and non-invertible inference rules.
The focused proof system of Andreoli for linear logic has been applied to both
the proof search and the proof normalization approaches to computation. Various
proof systems in literature exhibit characteristics of focusing to one degree
or another. We present a new, focused proof system for intuitionistic logic,
called LJF, and show how other proof systems can be mapped into the new system
by inserting logical connectives that prematurely stop focusing. We also use
LJF to design a focused proof system for classical logic. Our approach to the
design and analysis of these systems is based on the completeness of focusing
in linear logic and on the notion of polarity that appears in Girard's LC and
LU proof systems
Evaluating Knowledge Representation and Reasoning Capabilites of Ontology Specification Languages
The interchange of ontologies across the World Wide Web (WWW) and the cooperation among heterogeneous agents placed on it is the main reason for the development of a new set of ontology specification languages, based on new web standards such as XML or RDF. These languages (SHOE, XOL, RDF, OIL, etc) aim to represent the knowledge contained in an ontology in a simple and human-readable way, as well as allow for the interchange of ontologies across the web. In this paper, we establish a common framework to compare the expressiveness of "traditional" ontology languages (Ontolingua, OKBC, OCML, FLogic, LOOM) and "web-based" ontology languages. As a result of this study, we conclude that different needs in KR and reasoning may exist in the building of an ontology-based application, and these needs must be evaluated in order to choose the most suitable ontology language(s)
Astro-WISE: Chaining to the Universe
The recent explosion of recorded digital data and its processed derivatives
threatens to overwhelm researchers when analysing their experimental data or
when looking up data items in archives and file systems. While current hardware
developments allow to acquire, process and store 100s of terabytes of data at
the cost of a modern sports car, the software systems to handle these data are
lagging behind. This general problem is recognized and addressed by various
scientific communities, e.g., DATAGRID/EGEE federates compute and storage power
over the high-energy physical community, while the astronomical community is
building an Internet geared Virtual Observatory, connecting archival data.
These large projects either focus on a specific distribution aspect or aim to
connect many sub-communities and have a relatively long trajectory for setting
standards and a common layer. Here, we report "first light" of a very different
solution to the problem initiated by a smaller astronomical IT community. It
provides the abstract "scientific information layer" which integrates
distributed scientific analysis with distributed processing and federated
archiving and publishing. By designing new abstractions and mixing in old ones,
a Science Information System with fully scalable cornerstones has been
achieved, transforming data systems into knowledge systems. This break-through
is facilitated by the full end-to-end linking of all dependent data items,
which allows full backward chaining from the observer/researcher to the
experiment. Key is the notion that information is intrinsic in nature and thus
is the data acquired by a scientific experiment. The new abstraction is that
software systems guide the user to that intrinsic information by forcing full
backward and forward chaining in the data modelling.Comment: To be published in ADASS XVI ASP Conference Series, 2006, R. Shaw, F.
Hill and D. Bell, ed
Data-driven backward chaining
The C Language Integrated Production System (CLIPS) cannot effectively perform sound and complete logical inference in most real-world contexts. The problem facing CLIPS is its lack of goal generation. Without automatic goal generation and maintenance, forward chaining can only deduce all instances of a relationship. Backward chaining, which requires goal generation, allows deduction of only that subset of what is logically true which is also relevant to ongoing problem solving. Goal generation can be mimicked in simple cases using forward chaining. However, such mimicry requires manual coding of additional rules which can assert an inadequate goal representation for every condition in every rule that can have corresponding facts derived by backward chaining. In general, for N rules with an average of M conditions per rule the number of goal generation rules required is on the order of N*M. This is clearly intractable from a program maintenance perspective. We describe the support in Eclipse for backward chaining which it automatically asserts as it checks rule conditions. Important characteristics of this extension are that it does not assert goals which cannot match any rule conditions, that 2 equivalent goals are never asserted, and that goals persist as long as, but no longer than, they remain relevant
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