We present a new method, "Expansion-Constrained Ordinary Least Squares" (ECOLS), that produces a linear approximation but also guarantees convergence when used ...
Our aim is to develop a variant of linear regression that, when used in a fitted value iteration al- gorithm, guarantees convergence of the algorithm to a fixed ...
Our aim is to develop a variant of linear regression that, when used in a fitted value iteration al- gorithm, guarantees convergence of the algorithm to a fixed ...
This work presents a new method, "Expansion-Constrained Ordinary Least Squares" (ECOLS), that produces a linear approximation but also guarantees ...
Dec 12, 2011 · We present a new method, "Expansion-Constrained Ordinary Least Squares" (ECOLS), that produces a linear approximation but also guarantees ...
Apr 1, 2019 · In Andrew Ng's fitted value iteration algorithm, which I gave the detail steps as below, it will try to find the best action of one state s(i) in step 3.
Convergent Fitted Value Iteration with Linear Function Approximation. Open in new window. Thumbnails Document Outline Attachments
Aug 5, 2018 · In this algorithm, we are approximating the value function V(s), over a finite number of states (s(1),s(2)...s(m)) using supervised learning algorithm like ...
We will prove convergence for a significant class of fitted temporal difference algorithms, including algo- rithms based on °-nearest-neighbor, linear interpola ...
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What is linear function approximation?
What is value function approximation in RL?
Vθk converges at a geometric rate (in || · ||π) to a solution of Vθ = ΠTVθ. Proposition 1 is established through a sequence of lemmas. The first is standard, ...