Shorten introduction in games.ipynb

chiragvartak · chiragvartak · commit 8165fd09b5c0 · 2016-03-14T17:33:02.000+05:30
diff --git a/games.ipynb b/games.ipynb
@@ -13,15 +13,17 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## An Introduction, and some other (un)essential information"
+    "## An Introduction"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "  Hello all!  \n",
-    "  In this IPython notebook, I plan to help you a little so that you will be able to use the [games.py](https://github.com/aimacode/aima-python/blob/master/games.py) module. You might already know that the `games.py` module implements the algorithms in Chapter 5 (Adversarial Search) of the book 'Artificial Intelligence: A Modern Approach'. The code in this IPython notebook, and the entire [aima-python](https://github.com/aimacode/aima-python) repository is intended to work with Python 3 (specifically, Python 3.4). So if you happen to be working on Python 2, you should switch to Python 3. If you do not have Python 3 installed, you might want to get that done first. Or even better, install [Anaconda](https://www.continuum.io/downloads) and you will get Jupyter Notebook and IPython along with it. This way you will be able to run both Python 2 and Python 3 using what they call 'virtual environments'. This is the way to go if you don't yet want to let go of your dear old Python 2.7. And this is what I do anyways.  \n",
+    "  In this IPython notebook, I plan to help you a little so that you will be able to use the [games.py](https://github.com/aimacode/aima-python/blob/master/games.py) module. You might already know that the `games.py` module implements the algorithms in Chapter 5 (Adversarial Search) of the book 'Artificial Intelligence: A Modern Approach'.  \n",
+    "  \n",
+    "  Before we begin, if you are unsure of how to use the [aima-python](https://github.com/aimacode/aima-python) repository or are not familiar with IPython notebooks you should read the [intro notebook](https://github.com/aimacode/aima-python/blob/master/intro.ipynb) first.\n",
     "  \n",
     "  What we will do to learn to use the code in this module is simply dive in! I feel this is the correct approach as I assume you must have already read Chapter 5 of AIMA. If you haven't, you might want to go back and do that first. If you are tired (or just lazy), at least read the chapter upto Sec. 5.3 because this module covers the algorithms only till that section anyway. So, I will start by explaining what the class `Game` is and then we will immediately start implementing the `TicTacToe` game. After we define the rules of the `TicTacToe` game, we will create AI players who use different search strategies, namely Minimax Search and Alpha-Beta Search. We will make these players play among themselves, and later on we ourselves will play against these AI players (Yay!).  \n",
     "  \n",
@@ -870,7 +872,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.1"
+   "version": "3.4.4"
   }
  },
  "nbformat": 4,
