Construct · 1 fields · 1 citations

MAXQ value function decomposition: a standalone construct

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Reinforcement learning

a hierarchical reinforcement learning method that splits a task into subtasks and decomposes the value function into the values of those subtasks.

In reinforcement learning, MAXQ value function decomposition refers to a hierarchical reinforcement learning method that splits a task into subtasks and decomposes the value function into the values of those subtasks. This meaning comes from Dietterich (2000) in Journal of Artificial Intelligence Research.[1]

Unit
Recovery means
Measured by

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Nearby constructs

function5 fields · 6 citationsjingle · one word, five constructs intelligence6 fields · 14 citationsjingle · one name, six constructs learning6 fields · 14 citationsjingle · one name, six constructs

References

Dietterich, T. G. (2000). Hierarchical Reinforcement Learning with the MAXQ Value Function Decomposition. Journal of Artificial Intelligence Research, 13, 227-303. https://doi.org/10.1613/jair.639

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