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Implement EXP3.R to tackle switching bandits ? #100

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Naereen opened this issue Dec 12, 2017 · 1 comment
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Implement EXP3.R to tackle switching bandits ? #100

Naereen opened this issue Dec 12, 2017 · 1 comment
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new algo I have to implement a new algorithm! Yay! non-stationary For non-stationary bandits simulations single-player For single-player bandits simulations

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Naereen commented Dec 12, 2017

@Naereen Naereen added the new algo I have to implement a new algorithm! Yay! label Dec 12, 2017
@Naereen Naereen self-assigned this Dec 12, 2017
@Naereen Naereen changed the title Implement EXP3.R ? Implement EXP3.R to tackle switching bandits ? Apr 25, 2018
@Naereen Naereen mentioned this issue Oct 2, 2018
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@Naereen Naereen added non-stationary For non-stationary bandits simulations single-player For single-player bandits simulations labels Oct 7, 2018
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Naereen commented Nov 21, 2018

Two variants of Exp3R have been implemented: Exp3.R uses naive Exp3 as a base, and Exp3.R uses Exp3++ as a base.
They both work similarly. Not so great, but they work.

  • Mean reward:
    figure_1

  • Mean regret:
    figure_1

Naereen added a commit that referenced this issue Nov 21, 2018
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Closing #100, I implemented Exp3R and Exp3RPlusPlus in Policies.CD_UC…
bcdce3e 
…B (Policies/CD_UCB.py)
@Naereen Naereen closed this as completed Nov 22, 2018
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new algo I have to implement a new algorithm! Yay! non-stationary For non-stationary bandits simulations single-player For single-player bandits simulations
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