If one parallels the development of computing paradigms as a metaphor and approximation of what human knowledge is, other than "procedural" (FORTRAN), "declarative" (strongly type languages), which in the first case gives a notion of time and change while in the other case gives relative specificity (domain-dependence) for instance, there would be other models such as:
- "reactive" (or event-driven) which models the set of action-reactions of knowledge,
- "rule-based" (logic programming, PROLOG), which simulates a decision model
- "query-based" (query languages, data-driven models, Google), which simulates question and answer models (oracle models)
- "consensus/agreement-based" (network protocols), which model well democratized games and opinion-based models
- "message-based" (message passing models), which models well communication
- "agent-driven" (multi-agent systems), which models complex systems
Those are the ones I can think of at the moment, each of which provide a perspective to a complex representation problem, that is, the representation of knowledge.
Yes, the representation problem is big for us all, whether we come from compSci or philosophy. Perhaps we need a psychologist's point of view on this?
I miss fuzzy based data processing. Human knowledge is never complete in any subject. So all strong formal queries will flop. Associative and fuzzy algorithms will succeed.
Did anyone say it was complete? Perhaps this was eluded to elsewhere? Perhaps even all disciplines combined cannot account for human knowledge.
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