Merge pull request #198 from pfeinsper/Pedro2712-patch-4

Update README.md

.github/workflows/env.yml

@@ -4,13 +4,9 @@ on:
   push:
     branches:
       - '*'
-    paths:
-      - 'DSSE/**/*'
   pull_request:
     branches:
       - '*'
-    paths:
-      - 'DSSE/**/*'
 
 jobs:
   test-env:

README.md

@@ -2,10 +2,11 @@
 
 # Drone Swarm Search
 
-Welcome to the Drone Swarm Search repository! Below are the status badges that reflect the current state of our workflows, helping you quickly understand what's happening in our project.
-
-## Workflow Status
+The Drone Swarm Search project is an environment, based on PettingZoo, that is to be used in conjunction with multi-agent (or single-agent) reinforcement learning algorithms. It is an environment in which the agents (drones), have to find the targets (shipwrecked people). The agents do not know the position of the target, and do not receive rewards related to their own distance to the target(s). However, the agents receive the probabilities of the target(s) being in a certain cell of the map. The aim of this project is to aid in the study of reinforcement learning algorithms that require dynamic probabilities as inputs. A visual representation of the environment is displayed below. To test the environment (without an algorithm), run `basic_env.py`.
 
+<p align="center">
+    <img src="https://raw.github.com/PFE-Embraer/drone-swarm-search/env-cleanup/docs/gifs/render_with_grid_gradient.gif" width="400" height="400" align="center">
+</p>
 
 ## Quick Start
 
@@ -19,15 +20,6 @@ Welcome to the Drone Swarm Search repository! Below are the status badges that r
 
 https://pypi.org/project/DSSE/
 
-## About
-
-The Drone Swarm Search project is an environment, based on PettingZoo, that is to be used in conjunction with multi-agent (or single-agent) reinforcement learning algorithms. It is an environment in which the agents (drones), have to find the targets (shipwrecked people). The agents do not know the position of the target, and do not receive rewards related to their own distance to the target(s). However, the agents receive the probabilities of the target(s) being in a certain cell of the map. The aim of this project is to aid in the study of reinforcement learning algorithms that require dynamic probabilities as inputs. A visual representation of the environment is displayed below. To test the environment (without an algorithm), run `basic_env.py`.
-
-<p align="center">
-    <img src="https://raw.github.com/PFE-Embraer/drone-swarm-search/env-cleanup/docs/gifs/render_with_grid_gradient.gif" width="400" height="400" align="center">
-</p>
-
-
 ## Outcome
 
 | If drone is found            | If drone is not found  |