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Line 60 of slimevolley_pro.js contains the "learned" behaviour in 140 floats: "gene":{"0":7.5719,"1":4.4285,"2":2.2716,"3":-0.3598,"4":-7.8189,"5":-2.5422,"6

by deepnet 11y ago

Line 60 of slimevolley_pro.js contains the "learned" behaviour in 140 floats: "gene":{"0":7.5719,"1":4.4285,"2":2.2716,"3":-0.3598,"4":-7.8189,"5":-2.5422,"6":-3.2034,"7":0.3935,"8":-6.7593,"9":-8.0551,"10":1.3679,"11":2.1859,"12":1.2202,"13":-0.49,"14":-0.0316,"15":0.5221,"16":0.7026,"17":0.4179,"18":-2.1689,"19":1.646,"20":-13.3639,"21":1.5151,"22":1.1175,"23":-5.3561,"24":5.0442,"25":0.8451,"26":0.3987,"27":-2.6158,"28":0.4318,"29":-0.7361,"30":0.5715,"31":-2.9501,"32":-3.7811,"33":-5.8994,"34":6.4167,"35":2.5014,"36":7.338,"37":-2.9887,"38":2.4586,"39":13.4191,"40":2.7395,"41":-3.9708,"42":1.6548,"43":-2.7554,"44":-1.5345,"45":-6.4708,"46":-4.4454,"47":-0.6224,"48":-1.0988,"49":4.4501,"50":9.2426,"51":-0.7392,"52":0.4452,"53":1.8828,"54":-2.6277,"55":-10.851,"56":-3.2353,"57":-4.4653,"58":-3.1153,"59":-1.3707,"60":7.318,"61":16.0902,"62":1.4686,"63":7.0391,"64":1.7765,"65":-4.9573,"66":-1.0578,"67":1.3668,"68":-1.4029,"69":-1.155,"70":2.6697,"71":-8.8877,"72":1.1958,"73":-3.2839,"74":-5.4425,"75":1.6809,"76":7.6812,"77":-2.4732,"78":1.738,"79":0.3781,"80":0.8718,"81":2.5886,"82":1.6911,"83":1.2953,"84":-5.5961,"85":2.174,"86":-3.5098,"87":-5.4715,"88":-9.0052,"89":-4.6038,"90":-6.7447,"91":-2.5528,"92":0.4391,"93":-4.9278,"94":-3.6695,"95":-4.8673,"96":-1.6035,"97":1.5011,"98":-5.6124,"99":4.9747,"100":1.8998,"101":3.0359,"102":6.2983,"103":-2.703,"104":1.5025,"105":6.1841,"106":-0.9357,"107":-4.8568,"108":-2.1888,"109":-4.1143,"110":-3.9874,"111":-0.0459,"112":4.7134,"113":2.8952,"114":-9.3627,"115":-4.685,"116":0.3601,"117":-1.3699,"118":9.7294,"119":11.5596,"120":0.1918,"121":3.0783,"122":-6.6828,"123":-5.4398,"124":-5.088,"125":3.6948,"126":0.0329,"127":-0.1362,"128":-0.1188,"129":-0.7579,"130":0.3278,"131":-0.977,"132":-0.9377,"133":2.2935,"134":-2.0353,"135":-1.7786,"136":5.4567,"137":-3.6368,"138":3.4996,"139":-0.0685} These are the weights on the connections between the inputs, neurons and outputs. Everything you need to know about how to win Slime Volleyball in 140 numbers !

_lce0 11y ago
> Everything you need to know about how to win Slime Volleyball in 140 numbers ! I know kung fu!
- hardmaru 11y ago
  haha, I like that. Yeah, there are a total of 140 weights/biases in the neural network. This stuff is not bleeding edge - just taking techniques popular in academia and industry many years ago to make a fun game mainly for my own educational purpose. Basically recently I saw a lot of work on AI's playing ATARI games and wanted to learn reinforcement learning techniques, and the best way to learn is to build a game! I put up a description of this sketch here: http://blog.otoro.net/2015/03/28/neural-slime-volleyball/ http://blog.otoro.net/2015/03/28/neural-slime-volleyball/ Basically, the agent's brain consists of 7 neurons (compared to 250k for an ant), which are connected to all the inputs. The inputs are the game states, like locations of agents and ball, and velocities. Each neuron is also connected to each other. The first 3 neurons control the neuron's output (it's motor function), like whether it hits the up, forward, or back button - the same function that a human game player can do. The other 4 neurons are hidden neurons responsible for any deeper computation or thought, and are fed back into the input with a time lag. I also graphed a slice of the neural network in real time on the screen just for effect. More for design effect if anything.
0xdeadbeefbabe 11y ago
How many numbers do you need? It isn't just a matter of trial and error is it?
- deepnet 11y ago
  The number of weights depends on the network architecture. In this case fully connected , 1 weight per connection . 16 inputs to 7 neurons + 7 neurons to 3 outputs + 7 biases 16x7 + 7x3 + 7 = 140 http://blog.otoro.net/wp-content/uploads/sites/2/2015/03/slime_rnn.png http://blog.otoro.net/wp-content/uploads/sites/2/2015/03/sli... The number of neurons is a decidable.
hardmaru 11y ago
Hi deepnet Do you mind helping me truncate the length of the message above with the number array? It's causing issues on browser sessions not word wrapping messages Thanks vm
- sgentle 11y ago
  If anyone else is having this issue, I fixed it like this: document.querySelector('style').innerHTML += '.comment p { max-width: 70vw; overflow: scroll; }'
- deepnet 11y ago
  Very sorry I have messed things up :( Unfortunately I have not got an edit or delete link so I am powerless to alter my mistake. If any mods* can help delete this rogue copypasta I would be appreciative. [relevant xkcd](https://xkcd.com/327/ https://xkcd.com/327/) *emailed support
  - dang 11y ago
    Sure. Fixed. For future reference: I fixed it by adding two spaces before the very long line. That makes it be formatted as code and not wrap.

by deepnet 11y ago

_lce0 11y ago

> Everything you need to know about how to win Slime Volleyball in 140 numbers ! I know kung fu!

hardmaru 11y ago
haha, I like that. Yeah, there are a total of 140 weights/biases in the neural network. This stuff is not bleeding edge - just taking techniques popular in academia and industry many years ago to make a fun game mainly for my own educational purpose. Basically recently I saw a lot of work on AI's playing ATARI games and wanted to learn reinforcement learning techniques, and the best way to learn is to build a game! I put up a description of this sketch here: http://blog.otoro.net/2015/03/28/neural-slime-volleyball/ http://blog.otoro.net/2015/03/28/neural-slime-volleyball/ Basically, the agent's brain consists of 7 neurons (compared to 250k for an ant), which are connected to all the inputs. The inputs are the game states, like locations of agents and ball, and velocities. Each neuron is also connected to each other. The first 3 neurons control the neuron's output (it's motor function), like whether it hits the up, forward, or back button - the same function that a human game player can do. The other 4 neurons are hidden neurons responsible for any deeper computation or thought, and are fed back into the input with a time lag. I also graphed a slice of the neural network in real time on the screen just for effect. More for design effect if anything.

0xdeadbeefbabe 11y ago

How many numbers do you need? It isn't just a matter of trial and error is it?

deepnet 11y ago
The number of weights depends on the network architecture. In this case fully connected , 1 weight per connection . 16 inputs to 7 neurons + 7 neurons to 3 outputs + 7 biases 16x7 + 7x3 + 7 = 140 http://blog.otoro.net/wp-content/uploads/sites/2/2015/03/slime_rnn.png http://blog.otoro.net/wp-content/uploads/sites/2/2015/03/sli... The number of neurons is a decidable.

hardmaru 11y ago

Hi deepnet Do you mind helping me truncate the length of the message above with the number array? It's causing issues on browser sessions not word wrapping messages Thanks vm

sgentle 11y ago
If anyone else is having this issue, I fixed it like this: document.querySelector('style').innerHTML += '.comment p { max-width: 70vw; overflow: scroll; }'
deepnet 11y ago
Very sorry I have messed things up :( Unfortunately I have not got an edit or delete link so I am powerless to alter my mistake. If any mods* can help delete this rogue copypasta I would be appreciative. [relevant xkcd](https://xkcd.com/327/ https://xkcd.com/327/) *emailed support
- dang 11y ago
  Sure. Fixed. For future reference: I fixed it by adding two spaces before the very long line. That makes it be formatted as code and not wrap.