Chemical structures of telocollinites and sporinites. 1. Differentiation between telocollinites and sporinites by the aromatic structures present in their pyridine extracts

Lithotypes of UK carboniferous coals have been characterized. The chemical structures present in pyridine extracts of four telocollinites and four associated sporinites separated from the lithotypes are described. As they consist of small molecules entrapped within a system of larger molecules, the extracts could be considered microcosms of the coals themselves. The smaller molecules have been separated into fractions soluble in hexane, benzene-methanol and methanol and analysed by gas chromatography-mass spectrometry. The larger molecules have been analysed by g.c.-m.s. after mild oxidation. Sporinites consist of alkyl chains probably containing ether linkages and substituted by aromatic, mainly benzene, rings amongst which alkanes, alkylphenols, alkylbenzenes and alkylnaphthalenes are entrapped. Alkylphenols were the aromatics present in highest concentration. Telocollinites contain the same types of smaller molecules, but alkylnaphthalenes were the dominant aromatics. The larger more rigid molecules present in the telocollinites were more aromatic than those in sporinites but differed from one telocollinite to another. The most strongly coking telocollinite possessed the simplest aromatic structure. At the start of pyrolysis the small embedded molecules form cells of fluid material within which hydroaromatics such as alkylnaphthalene transfer hydrogen. Sporinites break up and become fluid.     

Knowledge-support systems

The social role of information technology is analysed in order to provide a framework for reasonable requirements for knowledge support systems. The many different scientific and engineering communities targeted on the development of specific knowledge support technologies are noted, and the problems of integrating developments from different communities are highlighted. The architectures of current integrated knowledge support systems are analysed within the social framework and the strengths and weaknesses of current modules are evaluated. Major system developments in recent years are used to exemplify the analysis, and expected directions for future development are outlined. The framework, analyses and examples are used to define a structured requirements specification for future research and development related to knowledge support systems.     

Knowledge Management in Societies of Intelligent Adaptive Agents

A model is developed of the emergence of the knowledge level in asociety of agents where agents model and manage other agents as resources,and manage the learning of other agents to develop such resources. It isargued that any persistent system that actively creates the conditions forits persistence is appropriately modeled in terms of the rationalteleological models that Newell defines as characterizing the knowledgelevel. The need to distribute tasks in agent societies motivates suchmodeling, and it is shown that if there is a rich order relationship ofdifficulty on tasks that is reasonably independent of agents then it isefficient to model agents competencies in terms of their possessingknowledge. It is shown that a simple training strategy of keeping an agent'sperformance constant by allocating tasks of increasing difficulty as anagent adapts optimizes the rate of learning and linearizes the otherwisesigmoidal learning curves. It is suggested that this provides a basis forassigning a granularity to knowledge that enables learning processes to bemanaged simply and efficiently.     

Modeling practical reasoning

Knowledge modeling perspectives on knowledge acquisition suggest that it is reasonable to analyze knowledge bases as collections of models. This article focuses on those parts of the knowledge base that model the practical reasoning processes of human experts, and asks what properties those models might be expected to have. It surveys the general notion of a model and its connotations in information systems science. It analyze the structure of practical reasoning as a control process with information flows involving essential uncertainty and adaptivity, where robustness is more significant than optimality. Systemic considerations suggest that models of the relevant knowledge will consist of a collection of isolated productions, many of which will be concerned with avoidance rather than goal achievement. the relations of such models to role-limiting methods, generic tasks, and deep knowledge are discussed. Finally, the implications of the knowledge modeling perspectives for developments in knowledge acquisition are discussed. © 1993 John Wiley & Sons, Inc.     

Induction of ripple-down rules applied to modeling large databases

A methodology forthe modeling of large data sets is described which results in rule sets having minimal inter-rule interactions, and being simply maintained. An algorithm for developing such rule sets automatically is described and its efficacy shown with standard test data sets. Comparative studies of manual and automatic modeling of a data set of some nine thousand five hundred cases are reported. A study is reported in which ten years of patient data have been modeled on a month by month basis to determine how well a diagnostic system developed by automated induction would have performed had it been in use throughout the project.