Questions tagged [interpolation]
5 questions
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Reward interpolation between MDPs. Will an optimal policy on both ends stay optimal inside the interval?
Say I've got two Markov Decision Processes (MDPs):
$$\mathcal{M_0} = (\mathcal{S}, \mathcal{A}, P, R_0),\quad\text{and}\quad\mathcal{M}_1 = (\mathcal{S}, \mathcal{A}, P, R_1)$$
Both have the same set of states and actions, and the transition…
Kostya
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What's the nearest neighbor algorithm used for upsampling?
Additionally, by default, the UpSampling2D layer will use a nearest neighbor algorithm to fill in the new rows and columns. This has the effect of simply doubling rows and columns, as described and is specified by the ‘interpolation‘ argument set…
stoic-santiago
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Continuous state and continuous action Markov decision process time complexity estimate: backward induction VS policy gradient method (RL)
Model Description: Model based (assume known of the entire model) Markov decision process.
Time($t$): Finite horizon discrete time with discounting factor
State($x_t$): Continuous multi-dimensional state
Action($a_t$): Continuous multi-dimensional…
leodongxu
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Values in reinforcement learning equal to values calculated by interpolation?
Imagine a pentagon-shaped room. Inside there is a robot. There are no obstacles. It can only exit through corners and there are some rewards on the corners: e.g. 5, 4, 4, 3, 3. A reinforcement learning algorithm would find the values inside the…
AnraTAnraT
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Interpolating image to increase resolution before feeding it to a neural network
Interpolation is a common way to make an image fit the right input shape for a neural network.
But is there any point in using interpolation to make it easier for the network to learn?
I assume interpolation adds no extra information to the input;…
MattSt
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