From f132c0390b9b59f3c6eba862eea3766d69f3d947 Mon Sep 17 00:00:00 2001 From: Antonio Serrano Date: Mon, 25 Mar 2019 10:43:11 +0100 Subject: [PATCH 1/5] Proposal of Expected SARSA algorithm --- TD/Expected SARSA Solution.ipynb | 243 +++++++++++++++++++++++++++++++ 1 file changed, 243 insertions(+) create mode 100644 TD/Expected SARSA Solution.ipynb diff --git a/TD/Expected SARSA Solution.ipynb b/TD/Expected SARSA Solution.ipynb new file mode 100644 index 000000000..ba7e96fd5 --- /dev/null +++ b/TD/Expected SARSA Solution.ipynb @@ -0,0 +1,243 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "%matplotlib inline\n", + "\n", + "import gym\n", + "import itertools\n", + "import matplotlib\n", + "import numpy as np\n", + "import pandas as pd\n", + "import sys\n", + "\n", + "if \"../\" not in sys.path:\n", + " sys.path.append(\"../\") \n", + "\n", + "from collections import defaultdict\n", + "from lib.envs.windy_gridworld import WindyGridworldEnv\n", + "from lib import plotting\n", + "\n", + "matplotlib.style.use('ggplot')" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "env = WindyGridworldEnv()" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "def make_epsilon_greedy_policy(Q, epsilon, nA):\n", + " \"\"\"\n", + " Creates an epsilon-greedy policy based on a given Q-function and epsilon.\n", + " \n", + " Args:\n", + " Q: A dictionary that maps from state -> action-values.\n", + " Each value is a numpy array of length nA (see below)\n", + " epsilon: The probability to select a random action . float between 0 and 1.\n", + " nA: Number of actions in the environment.\n", + " \n", + " Returns:\n", + " A function that takes the observation as an argument and returns\n", + " the probabilities for each action in the form of a numpy array of length nA.\n", + " \n", + " \"\"\"\n", + " def policy_fn(observation):\n", + " A = np.ones(nA, dtype=float) * epsilon / nA\n", + " best_action = np.argmax(Q[observation])\n", + " A[best_action] += (1.0 - epsilon)\n", + " return A\n", + " return policy_fn" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "def sarsa(env, num_episodes, discount_factor=1.0, alpha=0.5, epsilon=0.1, expected=False):\n", + " \"\"\"\n", + " SARSA algorithm: On-policy TD control. Finds the optimal epsilon-greedy policy.\n", + " \n", + " Args:\n", + " env: OpenAI environment.\n", + " num_episodes: Number of episodes to run for.\n", + " discount_factor: Gamma discount factor.\n", + " alpha: TD learning rate.\n", + " epsilon: Chance the sample a random action. Float betwen 0 and 1.\n", + " expected: boolean to use Expected SARSA instead of regular SARSA.\n", + " \n", + " Returns:\n", + " A tuple (Q, stats).\n", + " Q is the optimal action-value function, a dictionary mapping state -> action values.\n", + " stats is an EpisodeStats object with two numpy arrays for episode_lengths and episode_rewards.\n", + " \"\"\"\n", + " \n", + " # The final action-value function.\n", + " # A nested dictionary that maps state -> (action -> action-value).\n", + " Q = defaultdict(lambda: np.zeros(env.action_space.n))\n", + " \n", + " # Keeps track of useful statistics\n", + " stats = plotting.EpisodeStats(\n", + " episode_lengths=np.zeros(num_episodes),\n", + " episode_rewards=np.zeros(num_episodes))\n", + "\n", + " # The policy we're following\n", + " policy = make_epsilon_greedy_policy(Q, epsilon, env.action_space.n)\n", + " \n", + " for i_episode in range(num_episodes):\n", + " # Print out which episode we're on, useful for debugging.\n", + " if (i_episode + 1) % 100 == 0:\n", + " print(\"\\rEpisode {}/{}.\".format(i_episode + 1, num_episodes), end=\"\")\n", + " sys.stdout.flush()\n", + " \n", + " # Reset the environment and pick the first action\n", + " state = env.reset()\n", + " action_probs = policy(state)\n", + " action = np.random.choice(np.arange(len(action_probs)), p=action_probs)\n", + " \n", + " # One step in the environment\n", + " for t in itertools.count():\n", + " # Take a step\n", + " next_state, reward, done, _ = env.step(action)\n", + " \n", + " # Pick the next action\n", + " next_action_probs = policy(next_state)\n", + " next_action = np.random.choice(np.arange(len(next_action_probs)), p=next_action_probs)\n", + " \n", + " # Update statistics\n", + " stats.episode_rewards[i_episode] += reward\n", + " stats.episode_lengths[i_episode] = t\n", + " \n", + " # TD Update\n", + " if expected:\n", + " expected_value = sum(policy(next_state)) * Q[next_state][next_action]\n", + " td_target = reward + discount_factor * expected_value\n", + " else:\n", + " td_target = reward + discount_factor * Q[next_state][next_action]\n", + " \n", + " td_delta = td_target - Q[state][action]\n", + " Q[state][action] += alpha * td_delta\n", + " \n", + " if done:\n", + " break\n", + " \n", + " action = next_action\n", + " state = next_state \n", + " \n", + " return Q, stats" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Episode 200/200." + ] + } + ], + "source": [ + "Q, stats = sarsa(env, 200, expected=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "(
,\n", + "
,\n", + "
)" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "plotting.plot_episode_stats(stats)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "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": "3.6.5" + } + }, + "nbformat": 4, + "nbformat_minor": 1 +} From dbb4f5a58893b632d10fd215b932f396dc49a1f7 Mon Sep 17 00:00:00 2001 From: Antonio Serrano Date: Mon, 25 Mar 2019 11:33:03 +0100 Subject: [PATCH 2/5] Proposal of Double Q-Learning algorithm --- TD/Double Q-Learning.ipynb | 244 +++++++++++++++++++++++++++++++++++++ 1 file changed, 244 insertions(+) create mode 100644 TD/Double Q-Learning.ipynb diff --git a/TD/Double Q-Learning.ipynb b/TD/Double Q-Learning.ipynb new file mode 100644 index 000000000..9207acc9e --- /dev/null +++ b/TD/Double Q-Learning.ipynb @@ -0,0 +1,244 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [], + "source": [ + "%matplotlib inline\n", + "\n", + "import gym\n", + "import itertools\n", + "import matplotlib\n", + "import numpy as np\n", + "import pandas as pd\n", + "import sys\n", + "\n", + "\n", + "if \"../\" not in sys.path:\n", + " sys.path.append(\"../\") \n", + "\n", + "from collections import defaultdict\n", + "from lib.envs.cliff_walking import CliffWalkingEnv\n", + "from lib import plotting\n", + "\n", + "matplotlib.style.use('ggplot')" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [], + "source": [ + "env = CliffWalkingEnv()" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [], + "source": [ + "def make_epsilon_greedy_policy(Q1, Q2, epsilon, nA):\n", + " \"\"\"\n", + " Creates an epsilon-greedy policy based on a given Q-function and epsilon.\n", + " \n", + " Args:\n", + " Q1, Q2: dictionaries that map from state -> action-values.\n", + " Each value is a numpy array of length nA (see below)\n", + " epsilon: The probability to select a random action . float between 0 and 1.\n", + " nA: Number of actions in the environment.\n", + " \n", + " Returns:\n", + " A function that takes the observation as an argument and returns\n", + " the probabilities for each action in the form of a numpy array of length nA.\n", + " \n", + " \"\"\"\n", + " def policy_fn(observation):\n", + " A = np.ones(nA, dtype=float) * epsilon / nA\n", + " best_action = np.argmax(Q1[observation] + Q2[observation])\n", + " A[best_action] += (1.0 - epsilon)\n", + " return A\n", + " return policy_fn" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [], + "source": [ + "def q_learning(env, num_episodes, discount_factor=1.0, alpha=0.5, epsilon=0.1):\n", + " \"\"\"\n", + " Q-Learning algorithm: Off-policy TD control. Finds the optimal greedy policy\n", + " while following an epsilon-greedy policy\n", + " \n", + " Args:\n", + " env: OpenAI environment.\n", + " num_episodes: Number of episodes to run for.\n", + " discount_factor: Gamma discount factor.\n", + " alpha: TD learning rate.\n", + " epsilon: Chance the sample a random action. Float betwen 0 and 1.\n", + " \n", + " Returns:\n", + " A tuple (Q, episode_lengths).\n", + " Q is the optimal action-value function, a dictionary mapping state -> action values.\n", + " stats is an EpisodeStats object with two numpy arrays for episode_lengths and episode_rewards.\n", + " \"\"\"\n", + " \n", + " # The two final action-value functions Q1 and Q2.\n", + " # A nested dictionary that maps state -> (action -> action-value).\n", + " Q1 = defaultdict(lambda: np.zeros(env.action_space.n))\n", + " Q2 = defaultdict(lambda: np.zeros(env.action_space.n))\n", + "\n", + " # Keeps track of useful statistics\n", + " stats = plotting.EpisodeStats(\n", + " episode_lengths=np.zeros(num_episodes),\n", + " episode_rewards=np.zeros(num_episodes)) \n", + " \n", + " # The policies we're following\n", + " policy = make_epsilon_greedy_policy(Q1, Q2, epsilon, env.action_space.n)\n", + " \n", + " for i_episode in range(num_episodes):\n", + " # Print out which episode we're on, useful for debugging.\n", + " if (i_episode + 1) % 100 == 0:\n", + " print(\"\\rEpisode {}/{}.\".format(i_episode + 1, num_episodes), end=\"\")\n", + " sys.stdout.flush()\n", + " \n", + " # Reset the environment and pick the first action\n", + " state = env.reset()\n", + " \n", + " # One step in the environment\n", + " # total_reward = 0.0\n", + " for t in itertools.count(): \n", + " \n", + " # Take a step\n", + " action_probs = policy(state)\n", + " action = np.random.choice(np.arange(len(action_probs)), p=action_probs)\n", + " next_state, reward, done, _ = env.step(action)\n", + "\n", + " # Update statistics\n", + " stats.episode_rewards[i_episode] += reward\n", + " stats.episode_lengths[i_episode] = t\n", + " \n", + " # TD Update\n", + " if np.random.binomial(1, 0.5, 1)==0:\n", + " best_next_action = np.argmax(Q1[next_state]) \n", + " td_target = reward + discount_factor * Q1[next_state][best_next_action]\n", + " td_delta = td_target - Q1[state][action]\n", + " Q1[state][action] += alpha * td_delta\n", + " else:\n", + " best_next_action = np.argmax(Q2[next_state]) \n", + " td_target = reward + discount_factor * Q2[next_state][best_next_action]\n", + " td_delta = td_target - Q2[state][action]\n", + " Q2[state][action] += alpha * td_delta\n", + " \n", + " if done:\n", + " break\n", + " \n", + " state = next_state\n", + " \n", + " return Q1, Q2, stats" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Episode 500/500." + ] + } + ], + "source": [ + "Q1, Q2, stats = q_learning(env, 500)" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "(
,\n", + "
,\n", + "
)" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "plotting.plot_episode_stats(stats)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "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": "3.6.5" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} From 19bc2dd5622933525c835a3b4ffdc48e654a2c3a Mon Sep 17 00:00:00 2001 From: Antonio Serrano Date: Mon, 25 Mar 2019 11:53:56 +0100 Subject: [PATCH 3/5] Typo in the updating rule --- TD/Double Q-Learning.ipynb | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/TD/Double Q-Learning.ipynb b/TD/Double Q-Learning.ipynb index 9207acc9e..dea6c9ea0 100644 --- a/TD/Double Q-Learning.ipynb +++ b/TD/Double Q-Learning.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 23, + "execution_count": 30, "metadata": {}, "outputs": [], "source": [ @@ -28,7 +28,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 35, "metadata": {}, "outputs": [], "source": [ @@ -37,7 +37,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 32, "metadata": {}, "outputs": [], "source": [ @@ -66,7 +66,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 33, "metadata": {}, "outputs": [], "source": [ @@ -126,12 +126,12 @@ " # TD Update\n", " if np.random.binomial(1, 0.5, 1)==0:\n", " best_next_action = np.argmax(Q1[next_state]) \n", - " td_target = reward + discount_factor * Q1[next_state][best_next_action]\n", + " td_target = reward + discount_factor * Q2[next_state][best_next_action]\n", " td_delta = td_target - Q1[state][action]\n", " Q1[state][action] += alpha * td_delta\n", " else:\n", " best_next_action = np.argmax(Q2[next_state]) \n", - " td_target = reward + discount_factor * Q2[next_state][best_next_action]\n", + " td_target = reward + discount_factor * Q1[next_state][best_next_action]\n", " td_delta = td_target - Q2[state][action]\n", " Q2[state][action] += alpha * td_delta\n", " \n", @@ -145,7 +145,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 34, "metadata": {}, "outputs": [ { From b369d9ae5999fe5ce615599745a214b1613404b2 Mon Sep 17 00:00:00 2001 From: Antonio Serrano Date: Wed, 18 Mar 2020 12:13:15 +0100 Subject: [PATCH 4/5] Update README.md --- README.md | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/README.md b/README.md index 82009e229..e241252b9 100644 --- a/README.md +++ b/README.md @@ -1,3 +1,7 @@ +### Important note +This repo is just a forked from [dennybritz/reinforcement-learning](https://github.com/dennybritz/reinforcement-learning) to help me studying the book of [Reinforcement Learning: An Introduction (2nd Edition)](http://incompleteideas.net/book/RLbook2018.pdf). I have barely contributed to this project (yet). + + ### Overview This repository provides code, exercises and solutions for popular Reinforcement Learning algorithms. These are meant to serve as a learning tool to complement the theoretical materials from From 228a951fd56c08217ee9b88e69c64968a85a0d3f Mon Sep 17 00:00:00 2001 From: Antonio Serrano Date: Wed, 18 Mar 2020 12:13:56 +0100 Subject: [PATCH 5/5] Update README.md --- README.md | 4 ---- 1 file changed, 4 deletions(-) diff --git a/README.md b/README.md index e241252b9..82009e229 100644 --- a/README.md +++ b/README.md @@ -1,7 +1,3 @@ -### Important note -This repo is just a forked from [dennybritz/reinforcement-learning](https://github.com/dennybritz/reinforcement-learning) to help me studying the book of [Reinforcement Learning: An Introduction (2nd Edition)](http://incompleteideas.net/book/RLbook2018.pdf). I have barely contributed to this project (yet). - - ### Overview This repository provides code, exercises and solutions for popular Reinforcement Learning algorithms. These are meant to serve as a learning tool to complement the theoretical materials from