{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# This Notebook will develop how to explain an Agent and assess its performance." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "It is recommended to have a look at the [0_basic_functionalities](0_basic_functionalities.ipynb) notebook before getting into this one." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Objective**\n", "\n", "This notebook will cover the basics of how to \"code\" an Agent that takes action on the powergrid. Examples will be given of \"expert agent\" that can take actions based on some fixed rules. More generic type of *Agent*, relying for example on machine learning / deep learning will be covered in the notebook [3_TrainingAnAgent](3_TrainingAnAgent.ipynb).\n", "\n", "This notebook will also cover the description of the *Observation* class, usefull to take some actions." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import os\n", "import sys\n", "import grid2op" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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