Posted by Denham on January 22, 2000 at 16:00:36:

In Reply to: KM -- Why Bother? posted by Reilly Atkinson on January 20, 2000 at 21:21:12:

Reilly asks, >>"why not call "knowledge aquisition" by its traditional and euphonious name, learning." There is a difference and a distinction between knowledge acquisition, as the term is used in by the artificial intelligence community and learning. Let's explore:

Knowledge acquisition:
Most often refers to the elicitation (gathering, extraction, validation) of rules and personal heuristics (tips, tricks, rule of thumb) used to build qualitative models for decision support. There is usually no training or self-adaptive function here. Common examples are rule-based expert systems for helping with complex scheduling or configuation issues.

Learning:
The ability of a system to adjust to novel inputs and to improve with practice and exposure to continuous inputs. Such systems can learn by being trained e.g. neural networks or via credit assignment and selection e.g. genetic algorithms. Learning often means there is the ability to autonomously adjust the (internal) representation and some way to score or judge the outcome.

It is difficult to imagine that one can have knowledge acquisition without some level of learning when humans are involved, but when we refer to artificial systems e.g. software agents or workflow routing, this is a very fundamental distinction. I agree we need to avoid obscure terms but recognize the power and the utility of creating distinctions that matter and clarify meaning as a useful knowledge and communication practice.

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Follow Ups:

• Re: Knowledge acquisition & learning Reilly Atkinson 01:59:10 01/23/00 (3)
  • On 'Artificial' and 'Real' Learning Yogesh Malhotra 19:07:49 01/23/00 (2)
    • Re: On 'Artificial' and 'Real' Learning Reilly Atkinson 16:11:55 01/25/00 (1)
      • Re: On 'Artificial' and 'Real' Learning Yogesh Malhotra 22:05:49 01/25/00 (0)

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