Limiting Extrapolation in Linear Approximate Value Iteration

NeurIPS 2019 Andrea ZanetteAlessandro LazaricMykel J. KochenderferEmma Brunskill

We study linear approximate value iteration (LAVI) with a generative model. While linear models may accurately represent the optimal value function using a few parameters, several empirical and theoretical studies show the combination of least-squares projection with the Bellman operator may be expansive, thus leading LAVI to amplify errors over iterations and eventually diverge... (read more)

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