Relational Sequence Learning
نویسندگان
چکیده
Sequential behavior and sequence learning is essential to intelligence. Often the elements of sequences exhibit an internal structure that can elegantly be represented using relational atoms. Applying traditional sequential learning techniques to such relational sequences requires either to ignore the internal structure or to put up with a combinatorial explosion in the model complexity. This chapter briefly reviews relational sequence learning and describes methods that have been developed such as data mining techniques, (hidden) Markov models, conditional random fields, dynamic programming and reinforcement learning techniques.
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