From c64a0c5eb75904cef4ed0239fb73ec3e01a2c6aa Mon Sep 17 00:00:00 2001 From: u8slvn Date: Fri, 30 Aug 2024 11:14:48 +0200 Subject: [PATCH] docs: update readme --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index e3fc767..9830e69 100644 --- a/README.md +++ b/README.md @@ -15,7 +15,7 @@ **Doggo** is a basic dog AI developed in Python and using pygame as a rendering engine. The dog just walks around the screen, changing states and direction randomly and dog's fur color is also picked randomly at start. State changes are based on a [Markov chain](https://en.wikipedia.org/wiki/Markov_chain), which is a simple model to represent a sequence of possible events in which the probability of each event depends only on the state attained in the previous event. -Here is a list of the dog states: *idle*, *idle and bark*, *walk*, *walk and bark*, *sit*, *sit and bark*, *lie down*, *lie down and bark*., *run*, *run and bark*, *stand*, *stand and bark*, *sleep*. +Here is a list of the dog states: `idle`, `idle and bark`, `walk`, `walk and bark`, `sit`, `sit and bark`, `lie down`, `lie down and bark`, `run`, `run and bark`, `stand`, `stand and bark`, `sleep`. **Project context**: A colleague of mine wanted to have a dog, but he couldn't because of lots of reasons. So I decided to make him a virtual dog and it was the opportunity for me to play with Markov chains.