{ "nbformat": 4, "nbformat_minor": 0, "metadata": { "colab": { "name": "EXP3 Toy Example", "version": "0.3.2", "provenance": [], "collapsed_sections": [], "include_colab_link": true }, "kernelspec": { "name": "python2", "display_name": "Python 2" } }, "cells": [ { "cell_type": "markdown", "metadata": { "id": "view-in-github", "colab_type": "text" }, "source": [ "[View in Colaboratory](https://colab.research.google.com/gist/Feryal/ddfe13322e7f2c6186f723f37c444a21/exp3-toy-example.ipynb)" ] }, { "metadata": { "id": "eXYcKcoLLbZb", "colab_type": "text" }, "cell_type": "markdown", "source": [ "# EXP3 Toy Example\n", "\n", "Run this notebook once to get it setup.\n", "\n", "Then modify the sliders to see different traces of EXP3 learning when using different reward probabilities for the 3 tasks." ] }, { "metadata": { "id": "Ojy-XYziL1Xm", "colab_type": "code", "colab": {}, "cellView": "form" }, "cell_type": "code", "source": [ "#@title Imports\n", "from __future__ import absolute_import\n", "from __future__ import division\n", "from __future__ import print_function\n", "\n", "import numpy as np\n", "import collections\n", "import seaborn as sns\n", "import matplotlib.pyplot as plt\n", "sns.set_context(\"poster\", font_scale=1.2)" ], "execution_count": 0, "outputs": [] }, { "metadata": { "id": "-iZ-EG7fL1Xr", "colab_type": "code", "colab": {}, "cellView": "form" }, "cell_type": "code", "source": [ "#@title Code for EXP3\n", "class TeacherExp3(object):\n", " \"\"\"Teacher with Exponential-weight algorithm for Exploration and Exploitation.\n", " \"\"\"\n", "\n", " def __init__(self, tasks, gamma=0.3):\n", " self._tasks = tasks\n", " self._n_tasks = len(self._tasks)\n", " self._gamma = gamma\n", " self._log_weights = np.zeros(self._n_tasks)\n", " \n", " \n", " @property\n", " def task_probabilities(self):\n", " weights = np.exp(self._log_weights - np.sum(self._log_weights))\n", " probs = ((1 - self._gamma)*weights / np.sum(weights) + \n", " self._gamma/self._n_tasks)\n", " return probs\n", "\n", " \n", " def get_task(self):\n", " \"\"\"Samples a task, according to current Exp3 belief.\n", " \"\"\"\n", " task_i = np.random.choice(self._n_tasks, p=self.task_probabilities)\n", " return self._tasks[task_i]\n", " \n", " \n", " def update(self, task, reward):\n", " \"\"\" Updates the weight of task given current reward observed\n", " \"\"\" \n", " task_i = self._tasks.index(task)\n", " reward_corrected = reward/self.task_probabilities[task_i]\n", " self._log_weights[task_i] += self._gamma*reward_corrected/self._n_tasks\n", " \n" ], "execution_count": 0, "outputs": [] }, { "metadata": { "id": "DofavMcyL1Xw", "colab_type": "code", "colab": { "base_uri": "https://localhost:8080/", "height": 354 }, "cellView": "form", "outputId": "1d559fbd-d58b-4c0f-fa96-382b7e95bf8a" }, "cell_type": "code", "source": [ "#@title Example of EXP3 learning on 3 tasks {run: \"auto\"}\n", "\n", "# Setup\n", "p1 = 0.28 #@param {type: \"slider\", min:0, max:1, step:0.01}\n", "p2 = 0.4 #@param {type: \"slider\", min:0, max:1, step:0.01}\n", "p3 = 0.22 #@param {type: \"slider\", min:0, max:1, step:0.01}\n", "gamma = 0.1 #@param {type: \"slider\", min:0, max:1, step:0.01}\n", "T = 200 #@param {type:\"integer\"}\n", "\n", "p_sum = p1+p2+p3\n", "p1 /= p_sum\n", "p2 /= p_sum\n", "p3 /= p_sum\n", "tasks_rewards = collections.OrderedDict((\n", " ('one', p1), ('two', p2), ('three', p3)))\n", "tasks = tasks_rewards.keys()\n", "\n", "# Train\n", "teacher = TeacherExp3(tasks, gamma=gamma)\n", "weights_all = np.empty((T, len(tasks)))\n", "arm_probs_all = np.empty((T, len(tasks)))\n", "\n", "for t in range(T):\n", " # pull an arm\n", " task = teacher.get_task()\n", " \n", " # Get reward\n", " reward = np.random.rand() < tasks_rewards[task]\n", " \n", " # update belief\n", " teacher.update(task, reward)\n", " \n", " weights_all[t] = teacher._log_weights\n", " arm_probs_all[t] = teacher.task_probabilities\n", " \n", "\n", "# Plot\n", "sns.set_style(\"darkgrid\", {'figure.facecolor': 'none'})\n", "with sns.color_palette(\"bright\"):\n", " f, ax = plt.subplots(1, 1, figsize=(10, 5))\n", " ax.plot(arm_probs_all, linewidth=2)\n", " ax.legend(tasks, loc='upper left', bbox_to_anchor=(1, 1))\n", " ax.set_xlabel('Steps')\n", " ax.set_ylabel('Probability of choosing arm')" ], "execution_count": 37, "outputs": [ { "output_type": "display_data", "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAvQAAAFRCAYAAAAb5TnWAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nKzEH9GZmZmZmJfb/dGDmkygnAUIAAAAASUVORK5CYII=\n", "text/plain": [ "<matplotlib.figure.Figure at 0x7efce83b02d0>" ] }, "metadata": { "tags": [] } } ] } ] }