http://robowiki.net/w/index.php?title=Thread:Talk:Oculus/Movement/reply_(30)&feed=atom&action=historyThread:Talk:Oculus/Movement/reply (30) - Revision history2024-03-29T12:36:11ZRevision history for this page on the wikiMediaWiki 1.34.1http://robowiki.net/w/index.php?title=Thread:Talk:Oculus/Movement/reply_(30)&diff=51014&oldid=prevSkilgannon: Reply to Movement2017-08-30T21:09:25Z<p>Reply to <a href="/wiki/Thread:Talk:Oculus/Movement/reply_(27)" title="Thread:Talk:Oculus/Movement/reply (27)">Movement</a></p>
<p><b>New page</b></p><div>You should be getting 99+% against Bot A. If not, you have bugs in your surfing, or you aren't even attempting to control your distances. Look to [[Komarious]] or [[CunobelinDC]] for help here, and make sure you are predicting the same escape angles you intend to move in.<br />
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Once you've done that, if you aren't getting 95% against Bot B, you might still have bugs in your surfing in the attribute collection, or you need to improve your learning. This is the most simple learning, a simple linear relationship between forward velocity and guess factor. If your learning algorithm can't quickly learn a simple linear relationship, you need to rethink it. I would suggest using a super simple learning (8 bins for the velocity value, plus a lower weighted "all the data") to make sure you have the attribute collection correct, then move on to fixing your learning.<br />
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Finally, you should be getting 90% against Bot C. This can only be improved by adding better attributes that you think might inadvertently model your near-wall and escape-angle behavior.<br />
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Hope this helps. Better scores are of course possible, but are very design specific. However with early non-DC versions of [[Cunobelin]] I was able to get a 99.9 - 96.8 - 95.1 score, and this was just BasicSurfer with segmented learning and distancing.</div>Skilgannon