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On-line Discovery of Temporal-Difference Networks

On-line Discovery of Temporal-Difference Networks

This video was recorded at 25th International Conference on Machine Learning (ICML), Helsinki 2008. We present an algorithm for on-line, incremental discovery of temporal-difference (TD) networks. The key contribution is the establishment of three criteria to expand a node in TD network: a node is expanded when the node is well-known, independent, and has a prediction error that requires further explanation. Since none of these criteria requires centralized calculation operations, they are easily computed in a parallel and distributed manner, and scalable for bigger problems compared to other discovery methods of predictive state representations. Through computer experiments, we demonstrate the empirical effectiveness of our algorithm.


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