Abstract
One of the old saws about learning in AI is that an agent can only learn what it can be told, i.e., the agent has to have a vocabulary for the target structure which is to be acquired by learning. What this vocabulary is, for various tasks, is an issue that is common to whether one is building a knowledge system by learning or by other more direct forms of knowledge acquisition. I long have argued that both the forms of declarative knowledge required for problem solving as well as problem-solving strategies are functions of the problem-solving task and have identified a family of generic tasks that can be used as building blocks for the construction of knowledge systems. In this editorial, I discuss the implication of this line of research for knowledge acquisition and learning.
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Chandrasekaran, B. Task-Structures, Knowledge Acquisition and Learning. Machine Learning 4, 339–345 (1989). https://doi.org/10.1023/A:1022658823707
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DOI: https://doi.org/10.1023/A:1022658823707