From 220e7ec9504d84c07a3f71a3e7efaf0dffc9af2e Mon Sep 17 00:00:00 2001
From: WLS2002 <64534280+WLS2002@users.noreply.github.com>
Date: Wed, 16 Oct 2024 16:03:19 +0800
Subject: [PATCH] fix typo in readme

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 06dcca0..1d08dbc 100644
--- a/README.md
+++ b/README.md
@@ -25,7 +25,7 @@ TensorNEAT has been selected to recieve the **[GECCO 2024 Best Paper Award](http
 Many thanks to everyone who has been supporting TensorNEAT, and we will remain committed to advancing TensorNEAT for future 'open-endedness'!
 
 ## Introduction
-TensorNEAT is a JAX-based libaray for NeuroEvolution of Augmenting Topologies (NEAT) algorithms, focused on harnessing GPU acceleration to enhance the efficiency of evolving neural network structures for complex tasks. Its core mechanism involves the tensorization of network topologies, enabling parallel processing and significantly boosting computational speed and scalability by leveraging modern hardware accelerators. TensorNEAT is compatible with the [EvoX](https://github.com/EMI-Group/evox/) framewrok.
+TensorNEAT is a JAX-based libaray for NeuroEvolution of Augmenting Topologies (NEAT) algorithms, focused on harnessing GPU acceleration to enhance the efficiency of evolving neural network structures for complex tasks. Its core mechanism involves the tensorization of network topologies, enabling parallel processing and significantly boosting computational speed and scalability by leveraging modern hardware accelerators. TensorNEAT is compatible with the [EvoX](https://github.com/EMI-Group/evox/) framework.
 
 ## Key Features
 - JAX-based network for neuroevolution: