Determining What to Learn Through Component-Task Modeling

Krulwich, Bruce; Birnbaum, Lawrence; Collins, Gregg

Determining What to Learn Through Component-Task Modeling

Bruce Krulwich, Lawrence Birnbaum, Gregg Collins

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Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence. Cognitive Modelling. Pages 439-446.

Abstract

Research in machine learning has typically addressed the problem .of how and when to learn, and ignored the problem of formulating learning tasks in the first place. This paper addresses this issue in the context of the CASTLE system, I that dynamically formulates learning tasks for a given situation. Our approach utilizes an explicit model of the decision-making process to pinpoint which system component should be improved. CASTLE can then focus the learning process on the issues involved in improving the performance of the particular component.

Bruce Krulwich, Lawrence Birnbaum, and Gregg Collins. 1995. Determining What to Learn Through Component-Task Modeling. In Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, IJCAI-95. IJCAI, 439–446. https://ijcai.org/proceedings/1995/58

@inproceedings{ijcai1995p58,
  title     = {Determining What to Learn Through Component-Task Modeling},
  author    = {Krulwich, Bruce and Birnbaum, Lawrence and Collins, Gregg},
  booktitle = {Proceedings of the Fourteenth International Joint Conference on
               Artificial Intelligence, {IJCAI-95}},
  publisher = {International Joint Conferences on Artificial Intelligence},
  editor    = {Chris S. Mellish},
  pages     = {439--446},
  year      = {1995},
  note      = {Cognitive Modelling},
  url       = {https://ijcai.org/proceedings/1995/58},
}

TY  - CPAPER
TI  - Determining What to Learn Through Component-Task Modeling
AU  - Krulwich, Bruce
AU  - Birnbaum, Lawrence
AU  - Collins, Gregg
T2  - Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, IJCAI-95
PB  - International Joint Conferences on Artificial Intelligence
PY  - 1995
SP  - 439
EP  - 446
UR  - https://ijcai.org/proceedings/1995/58
ER  -