51 lines
1.1 KiB
Julia
51 lines
1.1 KiB
Julia
using Random
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using Plots
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mutable struct Bandit
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p::Number #the win rate
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p_estimate::Number #How to estimate the win rate
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N::Number #Number of samples
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Bandit(p) = new(p,0,0)
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end
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function pull(ban::Bandit)
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return convert(Int,rand() < ban.p)
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end
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function update(ban::Bandit, x::Number) #x is a sample number
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ban.N += 1
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ban.p_estimate = ((ban.N - 1) * ban.p_estimate + x) / ban.N
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end
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function ucb(mean::Number,n::Number,nⱼ::Number)
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return mean + √(2*log(n) / nⱼ)
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end
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num_trials = 100000;
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ϵ = 0.1;
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bandit_probs = [0.2,0.5,0.75];
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bandits = [Bandit(p) for p in bandit_probs];
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rewards = zeros(num_trials);
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total_plays = 0;
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optimal_j = argmax([b.p for b in bandits]);
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for j in 1:size(bandits)[1]
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x = pull(bandits[j])
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total_plays += 1
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update(bandits[j],x)
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end
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for i in 1:num_trials
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j = argmax([ucb(b.p_estimate,total_plays,b.N) for b in bandits])
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x = pull(bandits[j])
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total_plays += 1
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update(bandits[j],x)
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rewards[i] = x
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end
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cumulative_average = cumsum(rewards) ./ Array(1:num_trials);
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plot(cumulative_average,xaxis=:log)
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plot!(ones(num_trials) .* max(bandit_probs...))
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