Quake Bots Rock The Prefrontal Cortex
0x4B writes "Some researchers from Vanderbilt University have used id Software's Quake III Arena to test a model of the human prefrontal cortex. The model was injected into the control systems of a Quake Bot, allowing it to flexibly adapt to changing enemy characteristics. The bot was required to identify the vulnerability of its enemies to different types of weaponry through repeated combat trials. Not only are the bots busy shooting each other relentlessly, but you can catch the action by joining the battle as an observer. Source code and Quake virtual
machines are available for download."
Sounds like they were caught playing quake during work hours, and had to make up an elaborate story :)
/. blurb, it's not that cool if all they can learn is what weapon is best.
nah just kidding.. But from the
they day the bot switches to grapple and follows PCs round laughing at their hopelessness all the while grappling them to death I'll know their finished.
Or shooting someone with shotgun cos they'll fall backwards into the lava.
Or camp under the stairs when their bored
etc.etc.etc.
There are places where the networks are not touching,and there are places where they are-Boeing's Lori Gunter
An interesting development, but if they really want to replace human players they still need algorithms for name-calling, complaining and cheating.
It seems like it is a little unclear to some people how to correctly run our mod (largely due to me leaving out significant details on the download page). It is intended as an experiment involving one learning bot utilizing the PFC model and two special dummy bots. You need to make sure you run the game using the map I made so that the bots have constant interaction. Using the command line listed on the download page, start the game, and then switch yourself over to be an observer. Run the following console command: /idscenario
/addannbot just like you would /addbot to put a learning bot in the mix. For best results, use a bot that doesnt suck. Now switch over to the learning bot's first person view to see the status of its Neural network and PFC layers changing as a result of its perception. Igor, its aliiive.
Now you have some very colorful dummy bots with unoriginal names running around doing nothing. But it gets better....
Use the console command
Now, there is no damage or death in the mod because we didnt want this to complicate the experiment. What you should see is a blue icon appear above an enemy that is hit. A deflected shot will bounce off like it hit the invulnerability sphere. When the bot hits, you will notice the little white box at the top of the network status overlay (upper right corner of the screen) go solid. This signals that the bot got a reward.
Directly under that are two yellow boxes, these represent how much the bot wants to choose each weapon (full is highest). Once the bot learns something you will notice these switching dramatically in response to the characteristics of its enemy. The bottom row of red boxes shows the characteristics of the current enemy (shield color, gun color, position, ID).
Now with all this information the bot tries to figure out what about its opponent is important in deciding how to kill it. The top row of yellow boxes at the left of the screen encodes what dimension the bot is considering, shield color, gun color, location, or ID(name). When the bot picks the right dimension, it can reliably slam its opponent with the right beam color. When it chooses the wrong dimension, it performs miserably until it gives up and explores something else.
Our experiment is set up such that the first correct dimension is shield color. After the bot figures it out the experiment will autoswitch to the ID dimension. When this happens you will see a message appear at the top of the screen in red. When its behaving well, the bot will catch on quickly.
Thanks for checking out the mod, and sorry about being late with this info. If you've got questions a lot is explained in the code walkthrough on the site, otherwise just ask me here. cheers,
-Tamer