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/BF00130718

Markdown

[Chandrasekaran. "Task-Structures, Knowledge Acquisition and Learning." Machine Learning, 1989.](https://mlanthology.org/mlj/1989/chandrasekaran1989mlj-taskstructures/) doi:10.1007/BF00130718

BibTeX

@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/}
}