Learning and development in neural networks: the importance of starting small

@article{Elman1993LearningAD,
  title={Learning and development in neural networks: the importance of starting small},
  author={J. Elman},
  journal={Cognition},
  year={1993},
  volume={48},
  pages={71-99}
}
  • J. Elman
  • Published 1993
  • Psychology, Medicine
  • Cognition
  • It is a striking fact that in humans the greatest learning occurs precisely at that point in time--childhood--when the most dramatic maturational changes also occur. This report describes possible synergistic interactions between maturational change and the ability to learn a complex domain (language), as investigated in connectionist networks. The networks are trained to process complex sentences involving relative clauses, number agreement, and several types of verb argument structure… CONTINUE READING

    Topics from this paper.

    Chunking mechanisms in human learning
    • 681
    • PDF
    Curriculum learning
    • 2,002
    • Highly Influenced
    • PDF
    Language acquisition in the absence of explicit negative evidence: how important is starting small?
    • 235
    • Highly Influenced
    • PDF
    Learning and development in neural networks – the importance of prior experience
    • 51
    • Highly Influenced
    • PDF
    Human simulations of vocabulary learning
    • 500
    • PDF
    Characteristics of dissociable human learning systems
    • 1,080
    • PDF
    Toward a connectionist model of recursion in human linguistic performance
    • 226
    Incrementality and Prediction in Human Sentence Processing
    • 227
    • Highly Influenced
    • PDF

    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 54 REFERENCES
    Finding Structure in Time
    • 8,419
    • PDF
    Maturational Constraints on Language Learning
    • 947
    Distributed Representations, Simple Recurrent Networks, and Grammatical Structure
    • 181
    • PDF
    The Cascade-Correlation Learning Architecture
    • 2,750
    • PDF
    Formal Principles of Language Acquisition
    • 1,121
    • PDF
    Context theory of classification learning.
    • 2,706
    • PDF