Task-Structures, Knowledge Acquisition and Learning
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.
Cite
Text
Chandrasekaran. "Task-Structures, Knowledge Acquisition and Learning." Machine Learning, 1989. doi:10.1007/BF00130718Markdown
[Chandrasekaran. "Task-Structures, Knowledge Acquisition and Learning." Machine Learning, 1989.](https://mlanthology.org/mlj/1989/chandrasekaran1989mlj-taskstructures/) doi:10.1007/BF00130718BibTeX
@article{chandrasekaran1989mlj-taskstructures,
title = {{Task-Structures, Knowledge Acquisition and Learning}},
author = {Chandrasekaran, B.},
journal = {Machine Learning},
year = {1989},
pages = {339-345},
doi = {10.1007/BF00130718},
volume = {4},
url = {https://mlanthology.org/mlj/1989/chandrasekaran1989mlj-taskstructures/}
}