Turns out, that last message was not "off-list" like I intended. Yes, you too could get a travel stipend for the next hackathon if you come up with a cool hack ahead of time! :)
There, I came clean! --------- Matt Taylor OS Community Flag-Bearer Numenta On Sun, Aug 25, 2013 at 10:17 PM, Matthew Taylor <[email protected]> wrote: > [off-list] > > Keith, > > Very cool idea. I would love you to come to our next hackathon. I think > it's going to be Nov 2-3 in San Francisco. I might be able to set you up > with a free hotel room or travel stipend. Let me know if you think you > might be able to make it. > > --------- > Matt Taylor > OS Community Flag-Bearer > Numenta > > > On Sun, Aug 25, 2013 at 7:31 PM, Matt Keith <[email protected]> wrote: > >> Since I live in Colorado and wasn't able to make it to the last >> hackathon, I held my own last night and came up with this little example. >> It is the classic text based skiing game where you have to move the skier >> left or right to keep him on the ski slope without hitting the trees. >> >> I have been very intrigued by the idea that motor control could be just >> another form of prediction. So I thought that I could train a model on a >> perfect run of the game and then use the predictions that it generates to >> move the skier in a live game. >> >> It starts by feeding the model 1000 lines of perfect skier positions in a >> ramdomly generated ski slope. A slope line consists of 80 characters with >> two trees as boundaries and the skier (hopefully) in the middle. >> >> | H | >> Tree Skier Tree >> >> The slope line is encoded as three integer values to pass into the model: >> the left tree position, the skier position, and the right tree position. >> >> Given the current ski slope line, we ask the model to predict the next >> skier position. If the position is greater than the current value, the >> skier is moved to the right one space. If the position is less than the >> current value, the skier is moved to the left one space. Otherwise, the >> skier position is left alone. >> >> You can download the code and play for yourself at: >> https://github.com/keithcom/nta_ski >> >> Building and running this test app has raised a few more questions for me. >> >> 1. Is there a string encoder yet? Originally, I wanted to just send the >> model the full ski slope line, but converted it to the int array to pass in >> scaler values. >> 2. The trained model seems to work for a little bit, but then stops as it >> keeps learning during the live run. I would like the model to "see" the >> results of it's prediction (i.e. how it moved the skier to complete the >> feedback loop), but I also want to have some kind of error value so it >> knows that it's prediction was not optimal. Does a mechanism like this >> exist in the current code? >> 3. Most of the model settings are just copied directly from the hotgym >> example. Should I change some of the values to work better in this >> scenario? >> 4. Any other comments or suggestions to improve the demonstration? >> >> Thanks, >> >> Matt >> >> >> _______________________________________________ >> nupic mailing list >> [email protected] >> http://lists.numenta.org/mailman/listinfo/nupic_lists.numenta.org >> > >
_______________________________________________ nupic mailing list [email protected] http://lists.numenta.org/mailman/listinfo/nupic_lists.numenta.org
