<story><title>Reinventing the Wheel: Discovering the Optimal Rolling Shape with PyTorch (2019)</title><url>https://blog.benwiener.com/programming/2019/04/29/reinventing-the-wheel.html</url></story><parent_chain></parent_chain><comment><author>matsemann</author><text>&amp;gt; &lt;i&gt;I parameterized the wheel as a twenty sided polygon with a variable radius for each vertex, ri.&lt;/i&gt;&lt;p&gt;Could this way of representing the problem (radius) introduce bias to the solution? It could probably make many kind of shapes, but it may need to overcome some huge local maxima in order to drastically change it to something else by tweaking multiple of the radii.&lt;p&gt;When writing my thesis on spoke patterns for bicycle wheels, one of the representations outperformed the others, as it had symmetry baked in. That could have made it not find some esoteric solutions (which is why I had multiple representations).</text></comment>
<story><title>Reinventing the Wheel: Discovering the Optimal Rolling Shape with PyTorch (2019)</title><url>https://blog.benwiener.com/programming/2019/04/29/reinventing-the-wheel.html</url></story><parent_chain></parent_chain><comment><author>kd5bjo</author><text>It’s interesting to note that the final result, though essentially circular, has an offset axle.  This certainly seems suboptimal, and it would’ve been nice to have some analysis of why this differs from the expected result.</text></comment>