The task rehearsal method of life-long learning: Overcoming impoverished data

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2338, Issue , 2002, Pages 90-101

  Silver, Daniel L ^a   Mercer, Robert E ^b  

^a ACADIA UNIVERSITY   (Canada)

^b UNIVERSITY OF WESTERN ONTARIO   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTER SCIENCE; COMPUTERS;

DOMAIN KNOWLEDGE; KNOWLEDGE RETENTION; LIFE LONG LEARNING; MULTIPLE TASKS; NETWORK REPRESENTATION; NEURAL NETWORK ALGORITHM; SECONDARY TASKS; TRAINING EXAMPLE;

LEARNING SYSTEMS;

EID: 84974659970     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-47922-8_8     Document Type: Conference Paper

References (11)

1. Yaser S. Abu-Mostafa. Hints. Neural Computation, 7:639–671, 1995. 92
2. Jonathan Baxter. Learning internal representations. Proceedings of the Eighth International Conference on Computational Learning Theory, 1995. 91
3. Richard A. Caruana. Multitask learning. Machine Learning, 28:41–75, 1997. 91, 95
4. Michael McCloskey and Neal J. Cohen. Catastrophic interference in connectionist networks: the sequential learning problem. The Psychology of Learning and Motivation, 24:109–165, 1989. 92
5. Tom M. Mitchell. Machine Learning. McGraw Hill, New York, NY, 1997. 91
6. Anthony V. Robins. Catastrophic forgetting, rehearsal, and pseudorehearsal. Connection Science, 7:123–146, 1995. 92
7. Daniel L. Silver. Selective Transfer of Neural Network Task Knowledge. PhD Thesis, Dept. of Computer Science, University of Western Ontario, London, Canada, June 2000. 91, 92, 95, 96, 101
8. Daniel L. Silver and Robert E. Mercer. The parallel transfer of task knowledge using dynamic learning rates based on a measure of relatedness. Connection Science Special Issue: Transfer in Inductive Systems, 8(2):277–294, 1996. 91
9. Daniel L. Silver and Robert E. Mercer. Selective functional transfer: Inductive bias from related tasks. Proceedings of the International Conference on Artificial Intelligence and Soft Computing (ASC2001), pages 182–189, 2001. 91, 92
10. Sebastian Thrun. Lifelong learning algorithms. Learning to Learn, pages 181–209, 1997. 90, 91
11. Paul E. Utgoff. Machine Learning of Inductive Bias. Kluwer Academc Publisher, Boston, MA, 1986. 91