File(s) under permanent embargo
Epistemological approach to the process of practice
journal contributionposted on 2008-12-01, 00:00 authored by Richard DazeleyRichard Dazeley, B H Kang
Systems based on symbolic knowledge have performed extremely well in processing reason, yet, remain beset with problems of brittleness in many domains. Connectionist approaches do similarly well in emulating interactive domains, however, have struggled when modelling higher brain functions. Neither of these dichotomous approaches, however, have provided many inroads into the area of human reasoning that psychology and sociology refer to as the process of practice. This paper argues that the absence of a model for the process of practise in current approaches is a significant contributor to brittleness. This paper will investigate how the process of practise relates to deeper forms of contextual representations of knowledge. While researchers and developers of knowledge based systems have often incorporated the notion of context they treat context as a static entity, neglecting many connectionists' work in learning hidden and dynamic contexts. This paper argues that the omission of these higher forms of context is one of the fundamental problems in the application and interpretation of symbolic knowledge. Finally, these ideas for modelling context will lead to the reinterpretation of situation cognition which makes a significant step towards a philosophy of knowledge that could lead to the modelling of the process of practice.
JournalMinds and machines
Pagination547 - 567
LocationDordrecht, The Netherlands
Publication classificationC Journal article; C1.1 Refereed article in a scholarly journal
Copyright notice2008, Springer Science+Business Media B.V.
Read the peer-reviewed publication
Dynamic contextEpistemologyHidden contextKnowledge based systemsKnowledge representationPhilosophy of knowledgeProcess of practiceSituation cognitionScience & TechnologyTechnologyComputer Science, Artificial IntelligenceComputer ScienceSITUATED ACTIONARTIFICIAL-INTELLIGENCEKNOWLEDGESYSTEMSCONTEXTSWORKCYC