What is recorded here?
Developed incremental prediction methods that update from differences between successive predictions and analysed their relation to supervised prediction and dynamic programming.
Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.
Scientific scope
The paper proves convergence and optimality only under stated special cases; this record does not transfer those guarantees to all later temporal-difference or reinforcement-learning algorithms.
Read the original work
- Sutton, Learning to Predict by the Methods of Temporal Differences
- Sutton 1988 temporal-difference paper copy
This English explanation is an editorial reading view. It does not replace the complete original work or certify its science.
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People and systems
Richard S. Sutton
The named authors contributed to this scoped work; individual effort shares and later applications are not assigned by the byline.
Research locations and affiliations
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Documented countries / regions: United States
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English catalogue narrative
Sutton: learning to predict by temporal differences
Developed incremental prediction methods that update from differences between successive predictions and analysed their relation to supervised prediction and dynamic programming.
Scientific scope
The paper proves convergence and optimality only under stated special cases; this record does not transfer those guarantees to all later temporal-difference or reinforcement-learning algorithms.
Reading status
This is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.
People and systems
Richard S. Sutton
The named authors contributed to this scoped work; individual effort shares and later applications are not assigned by the byline.