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@PtrMan PtrMan released this 14 Apr 13:22
· 39 commits to master since this release
r0.0.4
8598f6d

NarConSimpleWorld
A NAR(in this case ONA) can control a agent in a virtual world (simplified pong or a simplified shoot'em'up game) which is rendered as a virtual map.
The vision pipeline does:

  • convolution for edge detection (8 directions)
  • sampling of edges as symbolic points (by threshold) into set X
  • recognition of points as lines (not strictly necessary)
  • rendering of points of lines back to black/white image
  • cropping of rendered image for unsupervised classifier C by proposal positions (derived from X)

generation of region proposals:

  • cluster points from set X by proximity
  • clusters are proposals, used for classifier C, have center and extend. Proposals are represented as AABB's

classifier C:

  • unsupervised (as usual)
  • online learning(as usual)
  • try to find closest match by distance of stored classes
  • if not found -> create new class with new class id
  • if found -> return class id
Assets 2
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