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Neural Computation, Vol 9, 1403-1419, Copyright © 1997 by The MIT Press
ARTICLES |
Fernando J. Pineda
A representation-independent mean-field dynamics is presented for batched
TD(
). The task is learning to predict the outcome of an
indirectly observed absorbing Markov process. In the case of linear
representations, the discrete-time deterministic iteration is an affine map
whose fixed point can be expressed in closed form without the assumption of
linearly independent observation vectors. Batched linear TD(
)
is proved to converge with probability 1 for all
. Theory and
simulation agree on a random walk example.
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