Description: Preface. Part I: Overview Articles. 1. Learning to Learn: Introduction and Overview; S. Thrun, L. Pratt. 2. A Survey of Connectionist Network Reuse Through Transfer; L. Pratt, B. Jennings. 3. Transfer in Cognition; A. Robins. Part II: Prediction. 4. Theoretical Models of Learning to Learn; J. Baxter. 5. Multitask Learning; R. Caruana. 6. Making a Low-Dimensional Representation Suitable for Diverse Tasks; N. Intrator, S. Edelman. 7. The Canonical Distortion Measure for Vector Quantization and Function Approximation; J. Baxter. 8. Lifelong Learning Algorithms; S. Thrun. Part III: Relatedness. 9. The Parallel Transfer of Task Knowledge Using Dynamic Learning Rates Based on a Measure of Relatedness; D.L. Silver, R.E. Mercer. 10. Clustering Learning Tasks and the Selective Cross-Task Transfer of Knowledge; S. Thrun, J. O'Sullivan. Part IV: Control. 11. CHILD: A First Step Towards Continual Learning; M.B. Ring. 12. Reinforcement Learning with Self-Modifying Policies; J. Schmidhuber, et al. 13. Creating Advice-Taking Reinforcement Learners; R. Maclin, J.W. Shavlik. Contributing Authors. Index.

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