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@greenwolf-nsk
Created August 9, 2018 16:11
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Bandits simulation
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"ExecuteTime": {
"end_time": "2018-08-09T16:03:28.844168Z",
"start_time": "2018-08-09T16:03:28.350034Z"
}
},
"outputs": [],
"source": [
"%matplotlib inline\n",
"%config InlineBackend.figure_format = 'retina'\n",
"\n",
"import random\n",
"\n",
"import numpy as np\n",
"import seaborn as sns\n",
"from matplotlib import pyplot as plt"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"ExecuteTime": {
"end_time": "2018-08-09T16:03:29.101707Z",
"start_time": "2018-08-09T16:03:28.846020Z"
}
},
"outputs": [],
"source": [
"class BernoulliEnv:\n",
" \n",
" def __init__(self, arms_proba: list):\n",
" self.arms_proba = arms_proba\n",
" \n",
" @property\n",
" def n_arms(self):\n",
" return len(self.arms_proba)\n",
" \n",
" def pull_arm(self, arm_id: int):\n",
" if random.random() < self.arms_proba[arm_id]:\n",
" return 1\n",
" else:\n",
" return 0 \n",
" \n",
"class Strategy:\n",
" \n",
" def __init__(self, n_arms: int):\n",
" self.n_arms = n_arms\n",
" self.n_iters = 0\n",
" self.arms_states = np.zeros(n_arms)\n",
" self.arms_actions = np.zeros(n_arms)\n",
" \n",
" def flush(self):\n",
" self.n_iters = 0\n",
" self.arms_states = np.zeros(self.n_arms)\n",
" self.arms_actions = np.zeros(self.n_arms)\n",
" \n",
" def update_reward(self, arm: int, reward: int):\n",
" self.n_iters += 1\n",
" self.arms_states[arm] += reward\n",
" self.arms_actions[arm] += 1\n",
" \n",
" def choose_arm(self):\n",
" raise NotImplementedError\n",
" \n",
" \n",
"class ABtest(Strategy):\n",
" \n",
" def __init__(self, n_arms: int, test_iters: int = 1000):\n",
" super().__init__(n_arms)\n",
" self.test_iters = test_iters\n",
" \n",
" def choose_arm(self):\n",
" if self.n_iters < self.test_iters:\n",
" return random.randint(0, self.n_arms - 1)\n",
" else:\n",
" return np.argmax(self.arms_states / self.arms_actions)\n",
" \n",
" \n",
"class EpsGreedy(Strategy):\n",
" \n",
" def __init__(self, n_arms: int, eps: float = 0.1):\n",
" super().__init__(n_arms)\n",
" self.eps = eps\n",
" \n",
" def choose_arm(self):\n",
" \n",
" if random.random() < self.eps:\n",
" return random.randint(0, self.n_arms - 1)\n",
" else:\n",
" return np.argmax(self.arms_states / self.arms_actions)\n",
" \n",
" \n",
"class UCB1(Strategy):\n",
" \n",
" def choose_arm(self):\n",
" if self.n_iters < self.n_arms:\n",
" return self.n_iters\n",
" else:\n",
" return np.argmax(self.ucb())\n",
" \n",
" \n",
" def ucb(self):\n",
" ucb = self.arms_states / self.arms_actions\n",
" ucb += np.sqrt(2 * np.log(self.n_iters) / self.arms_actions)\n",
" return ucb\n",
" \n",
" \n",
"class Bayesian(Strategy):\n",
" \n",
" def __init__(self, n_arms: int):\n",
" super().__init__(n_arms)\n",
" self.alphas = np.ones(self.n_arms)\n",
" self.betas = np.ones(self.n_arms)\n",
" \n",
" def choose_arm(self):\n",
" arm = np.argmax([np.random.beta(self.alphas[i], self.betas[i]) for i in range(self.n_arms)])\n",
" return arm\n",
" \n",
" def update_reward(self, arm: int, reward: int):\n",
" super().update_reward(arm, reward)\n",
" self.alphas[arm] += reward\n",
" self.betas[arm] += 1 - reward\n",
" \n",
" \n",
"class Bandit:\n",
" \n",
" def __init__(self, env: BernoulliEnv, strategy: Strategy):\n",
" self.env = env\n",
" self.strategy = strategy\n",
" \n",
" def action(self):\n",
" arm = self.strategy.choose_arm()\n",
" reward = self.env.pull_arm(arm)\n",
" self.strategy.update_reward(arm, reward) \n",
" "
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {
"ExecuteTime": {
"end_time": "2018-08-09T16:07:26.283294Z",
"start_time": "2018-08-09T16:07:26.278087Z"
}
},
"outputs": [],
"source": [
"# setup environment and strategies\n",
"be = BernoulliEnv([0.3, 0.5, 0.7])\n",
"ab = ABtest(be.n_arms, 1000)\n",
"eps = EpsGreedy(be.n_arms, 0.1)\n",
"ucb = UCB1(be.n_arms)\n",
"thompson = Bayesian(be.n_arms)"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {
"ExecuteTime": {
"end_time": "2018-08-09T16:07:01.229882Z",
"start_time": "2018-08-09T16:07:01.219122Z"
}
},
"outputs": [],
"source": [
"def calculate_regret(env: BernoulliEnv, strategy: Strategy, n_iters=20000):\n",
" strategy.flush()\n",
" bandit = Bandit(env, strategy)\n",
" regrets = []\n",
" for i in range(n_iters):\n",
" reward = bandit.strategy.arms_actions.dot(env.arms_proba)\n",
" optimal_reward = np.max(env.arms_proba) * i\n",
" regret = optimal_reward - reward\n",
" regrets.append(regret)\n",
" bandit.action()\n",
" \n",
" return regrets"
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {
"ExecuteTime": {
"end_time": "2018-08-09T16:07:59.462083Z",
"start_time": "2018-08-09T16:07:57.567799Z"
}
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/slauncher/.virtualenvs/rec/lib/python3.6/site-packages/ipykernel_launcher.py:60: RuntimeWarning: invalid value encountered in true_divide\n"
]
}
],
"source": [
"ab_regrets = calculate_regret(be, ab)\n",
"eps_regrets = calculate_regret(be, eps)\n",
"ucb_regrets = calculate_regret(be, ucb)\n",
"thompson_regrets = calculate_regret(be, thompson)"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {
"ExecuteTime": {
"end_time": "2018-08-09T16:07:03.765200Z",
"start_time": "2018-08-09T16:07:03.492762Z"
},
"scrolled": false
},
"outputs": [
{
"data": {
"text/plain": [
"Text(0,0.5,'cumulative regret (less is better)')"
]
},
"execution_count": 39,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f774f2907f0>"
]
},
"metadata": {
"image/png": {
"height": 372,
"width": 390
}
},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(6, 6))\n",
"plt.plot(ab_regrets, label='ab')\n",
"plt.plot(eps_regrets, label='eps')\n",
"plt.plot(ucb_regrets, label='ucb')\n",
"plt.plot(thompson_regrets, label='bayes')\n",
"plt.legend()\n",
"plt.xlabel('number of iterations')\n",
"plt.ylabel('cumulative regret (less is better)')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.4"
},
"toc": {
"nav_menu": {
"height": "12px",
"width": "252px"
},
"number_sections": true,
"sideBar": true,
"skip_h1_title": false,
"title_cell": "Table of Contents",
"title_sidebar": "Contents",
"toc_cell": false,
"toc_position": {},
"toc_section_display": "block",
"toc_window_display": false
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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