apostolique / agar.io-bot Goto Github PK
View Code? Open in Web Editor NEWThe aim of the project is to create a bot that can play Agar.io
License: MIT License
The aim of the project is to create a bot that can play Agar.io
License: MIT License
Please make the code more human readable.
It seems like the script does not work with Google Chrome using TamperMonkey. The script is loaded, but it does not appear to do anything.
This is a pretty big issue and possibly life threatening.
Here you go https://www.youtube.com/watch?v=j13H5Pgx7mk
So you remember when you were talking about a white-list in chat? Well what if we also have a running black-list, for example the bot is playing the game, it's doing it's job eating food/players, getting bigger.. escaping etc.. then all of a sudden some guy comes along and splits on it and it has to start over, well if we could then grab that players name then give any blob with that name a radius of no access depending on size, so that way no matter what direction that player is going if the bot comes in contact with said radius it escapes the best way it can.
Just a thought, I hope you get what I mean here.
-b3ck
See https://github.com/volundr-/imabotlol
This bot uses a sampling technique to determine a best course vector based on quantifying risk. Seems to work quite well. Choosing distinct targets works fine, but I think the risk model can be faster and more accurate if tuned well.
I found that the bot would occasionally get stuck and crash my browser when moving near/into the bottom right corner.
Attempted to fix it myself, changed
if (player[0].y > 11180 - 1000 && badAngles.length > 0) {
to
if (player[0].y > 10200 && badAngles.length > 0) {
Did so for both bottom wall and right wall, seemed to fix the issue. Not sure why.
Edit: Found that during gameplay the walls will seem to change position and move into the level, causing the above issue to repeat. Doing more research.
For bottom and right walls, chaged
var newY = 11180 + 100 + screenDistance();
to
var newX = 11350 + screenDistance();
Seems to be okay now.
The bot seems to have a lot of trouble sensing the boundaries of the room. Making the boundaries appear as an enemy would help.
It would be cool to add a feature that allows you to type in a username and once you reach a certain mass that you decide it feeds the selected user. It will then repeat.
For obvious reasons, the project being new doesn't mean the targeting system is absolutely 100% on point. Here are some obvious ones. Feel free to post other findings.
@Apostolique is planning on revamping the targeting system to combat this.
When script is enabled, no option to change name or server. Stuck on screen showing blobs moving in the background, there is no user blob.
http://i.gyazo.com/45d5c4fcf0a49ba7c8162f52bed82a2a.png
have the current version of the bot in the bottom right corner ("v0.2"). As well has having the bot check for updates every time it load up so you know if an update has been pushed out. This can simply be done by loading a txt file hosted on a website and checking if its current version is the same etc
I think this will have it a lot easier to know when an update is pushed out
The splits seem to still be working even when "t" is toggled off
A nice new evading algorithm could be easily done like this:
Have a "Spike ball" around the player, when any threat intersects a line of the spiky ball: render that line(direction) unusable and use the other lines as free areas to go.
Demonstration:
The red lines are intersected by threats, means we can't go that direction.
Green lines are not intersected, we can evade to this direction
Blue line is the invisible wall, if a line intersects this: it's a no-go.
http://puu.sh/hL6NZ/7f7b94a697.png
You could play around with the length of the lines to make it evade from further away.
Sorry for the crappy paint skills, hopefully you still get the point.
Is it possible to have a server selector implemented?
Since there a a few servers under each category, that would mean that you could play with your friends, without needing to keep refreshing until you are both on the save server
The server I was on just restarted (i think :o) and the shown score is still 702 from before!
It has many problems with detecting enemies and the danger areas are often way too small. Every single time the bot dies, it has been due to it simply jumping head-first right into an oncoming enemy. It does not seem to be able to detect many of the larger cells.The danger areas are often way too small because the bot's cell will only run from enemies 10 times its size when it is halfway through getting eaten by it.
A nice thing to do is to spawn many bots and when one of the "enemies" is one of your bots, you just eat it or get eaten.
What do you think?
Play a sound when something very important happens, example : the prediction system detects that the probability of death is growing too fast (escapes routes and possibilities diminishing, losing mass too fast, surrounded by enemies / cornered)
can we please get more comments in this code. I understand why we cant deobfuscate this but can we just get comments explaining what the variables are and what the functions do. that would be very helpful.
PS Thank you for starting this project.
I have set everything up right as far as i have read, but nothing happens. The script is enabled and everything.
Dear Maker of this Super Cool Hack. Hoperfully you read this fast. So i think that Agar.io just got updated and your Super Cool Hack doesn't work anymore (Image: : http://puu.sh/i7bIH/3e023f182a.png). Read this Story (if you want): I was searching for a Hack/Bot for Agar.io then i found a Video (not this Video). and it actually worked. i posted it on another video, where you "must" like comment subscribe or something and then he sends you the hack, yeah so i wanted that the Viewers dont get ripped off. The Next time i was on agar.io, well this happend: http://puu.sh/i7bIH/3e023f182a.png.
Greetings from Switzerland (i was from Switzerland all along m8)
Can you make them be able to work together?
When eating at the very edge of the world and then seeing an enemy, the AI will ignore the wall and try to escape through it, causing it to get stuck and eventually eaten.
This happens in the latest builds. Haven't checked the other walls yet.
please help meee or usss ;-;
Implement team mode :
Often I notice myself getting cornered in the red zone. The bot then has no idea how to get out.
The only issue i have with this script is the splinting. Because of it i can't get big :c and i want to get biggg :C Cool script tho :D
Would be nice if there's an option to ignore the split danger zone if a blob is X% bigger than you. Pretty much most of the time, unless you're close to the same size, they'll ignore you, so it's relatively safe to zip around the massive blobs.
There seems to be a point where an enemies red avoidance triangle becomes the entire size of the screen (happens a lot when you are near a large enemy and around 150 in size) and it will get stuck in avoiding these triangles even though there might not be a large enemy even close. This might be to account for split distance, but it is way way to far in a lot of cases and really can mess up the bot when you get in the middle of 2-3 of these.
the bot looks like dont like the taste of the others players
Yesterday the bot was running extremely smooth, even running the bot in 10 tabs on Firefox. Today, even just 1 tab running the bot (with no apps open) and the bot is very jittery. The bot will pause for several seconds before making a move. Going in manual mode and trying to move around, same issue. Seems like a huge lag. Not sure if its the bot or me or the connection. Any ideas?
Hi, where I can insert the boundaries of the canvas? To change the motion vector in the opposite direction.
Agar Server Selector allows you to join a specific ip address in order to play with your friends.
I'd like to see you make it so that you can run both plugins simultaneously, which currently doesn't work.
Source for Agar Server Selector: https://github.com/electronoob/agarmods
Is it possible to create a version to work for ViolentMonkey for Opera broswer?
The bot seems to ignore world borders and just continue to rub against the wall. This may be hard to fix, I have no idea.
In Firefox the play button wouldn't highlight to let me play so I had to change the HTML. Once I did press it, the game looked like this:
http://postimg.org/image/vc2h7chnp/
I noticed through 8 hours play or so, that it doesn't give priority to escape when there's a chance someone could split on you. It would be nice adding that.
Could you make some sort of documentation that would allow us to add our own behaviors. Most of your functions and variables have meaningless names and don't make a whole lot of sense to a reader. I'd like to have bots that find and feed certain players.
You should put all shortcut keys on the readme so people know what to use: e.g
T = toggle bot on/off
R = toggles lines on/off
Etc
i downloaded all the things to make that hack work (i only installed greasemonkey and the script) and the hack make that : "data:image/png;base64,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" (yes, the link of the image is long) so....can u update the hack? :)
Basically, my idea was this,
With the mod installed you can't see the leaderboard of what color is the dominant one on TeamPlay. I think it's an issue with the mod. No?
I'm spawning in the corner everytime and the script is lagging also the game isn't working with the bot. It appears to be something on line 1404. (gustoughson version), tried this version too and didn't work.
Can someone confirm? Firefox latest with greasemonkey latest version.
Enhancement
I thought there should maybe be a toggle showing what the bot's current tasks are, such as "Currently finding food" "Chasing prey" "Escaping threat" "In manual control", that kinda thing.
Since the bot is a little simplistic regarding what it has to do, there shouldn't be too many things required for the console other than to actually make a box showing the console.
So i installed all of this and now this is what happened
http://puu.sh/i7bIH/3e023f182a.png
Someone PLEASE help me!!!!
A declarative, efficient, and flexible JavaScript library for building user interfaces.
๐ Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. ๐๐๐
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google โค๏ธ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.