From e6004bd0abfecd6a57f22e021e464fd73afff537 Mon Sep 17 00:00:00 2001 From: Chinmaya Pancholi Date: Fri, 3 Mar 2017 22:23:20 +0530 Subject: [PATCH] Fixes typos in the search.ipynb --- search.ipynb | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/search.ipynb b/search.ipynb index 77bbc91bf..7f4fe7473 100644 --- a/search.ipynb +++ b/search.ipynb @@ -28,9 +28,9 @@ "source": [ "## Review\n", "\n", - "Here, we learn about problem solving. Building goal-based agents that can plan ahead to solve problems, in particular navigation problem / route finding problem. First, we will start the problem solving by precicly defining **problems** and their **solutions**. We will look at several general-purpose search algorithms. Broadly, search algorithms are classified into two types:\n", + "Here, we learn about problem solving. Building goal-based agents that can plan ahead to solve problems, in particular navigation problem / route finding problem. First, we will start the problem solving by precisely defining **problems** and their **solutions**. We will look at several general-purpose search algorithms. Broadly, search algorithms are classified into two types:\n", "\n", - "* **Uninformed search algorithms**: Search algorithms which explores the search space without having any information aboout the problem other than its definition.\n", + "* **Uninformed search algorithms**: Search algorithms which explores the search space without having any information about the problem other than its definition.\n", "* Examples:\n", " 1. Breadth First Search\n", " 2. Depth First Search\n", @@ -96,7 +96,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "We will use the abstract class `Problem` to define out real **problem** named `GraphProblem`. You can see how we defing `GraphProblem` by running the next cell." + "We will use the abstract class `Problem` to define our real **problem** named `GraphProblem`. You can see how we defing `GraphProblem` by running the next cell." ] }, { @@ -156,7 +156,7 @@ "collapsed": true }, "source": [ - "It is pretty straight forward to understand this `romania_map`. The first node **Arad** has three neighbours named **Zerind**, **Sibiu**, **Timisoara**. Each of these nodes are 75, 140, 118 units apart from **Arad** respectively. And the same goes with other nodes.\n", + "It is pretty straightforward to understand this `romania_map`. The first node **Arad** has three neighbours named **Zerind**, **Sibiu**, **Timisoara**. Each of these nodes are 75, 140, 118 units apart from **Arad** respectively. And the same goes with other nodes.\n", "\n", "And `romania_map.locations` contains the positions of each of the nodes. We will use the straight line distance (which is different from the one provided in `romania_map`) between two cities in algorithms like A\\*-search and Recursive Best First Search.\n", "\n", @@ -392,7 +392,7 @@ "* Currently exploring node - red\n", "* Already explored nodes - gray\n", "\n", - "Now, we will define some helper methods to display interactive buttons ans sliders when visualising search algorithms." + "Now, we will define some helper methods to display interactive buttons and sliders when visualising search algorithms." ] }, {