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Human resource machine year 32
Human resource machine year 32




human resource machine year 32 human resource machine year 32

So a hack came to my mind: Let's create a hopefully(!) high enough offset! (But how? And from what? And how high? - I later realized most negative numbers are around -1 to -10, if at all, or max -1 to -20. I tried various ways, because my algorithm would fail if fed with any <0 numbers. And it was fine until those damn "values of oppositely signed opportunity" came along. The main algorithm is from "SORT INIT" until "SORT DONE!". However in the end I enjoy this solution because I was so damn stuck on this level (ok, I will never ever get "Prime Factory" though!). Things went pretty much downhill from there.

human resource machine year 32

My solution and my algorithm was alright until I encountered negative numbers. How about heavily un-optimized silly versions? Including a dirty offset "hack"? (Commands: 65 / Steps: 241 / File under: genius, dumb and funny) K7Jmr9+dnLrNPkltO1Pikq0Mo2AUjIIhCQDzgh69 ĮJwTYGBgiOhQjPhSqxjBU/o6bkFuVaZ+Rn9FWWpqx4+UPzM+pYWsepH1fHt0vtGB3pKyQ/srtxwsrtuw T9iOFTEde7XiSo98Tll+8mDes5NtRde3T69jGAWjYIQCALCvddY ĮJzjYmBguGN/7aako+C1Js+Ti7b7XqtVDi07NC0y5AZQiuG8S+H+b77v9zKMglEwCoYlAABRvhGg ĮJwTYmBgOBHnXNAWf632WPya3T6xmd0+sfa5XHFGKY2JZumKuQGVPbGP2/Iydk5bkcUwRyXn3FKVHNHV Vb0lFaT/ZO+WyT097gundEquA/GNpm0weTDnu+WJpZXW79ftsPq+enrA5IXzW0ByBce8Pc7v6vOatPOS N/BeM1Arw6lSFmeRosm+4oXzw8IKX8d1lOUm2FVpxW2tXRL5vn52cG6DqL9ew1nPj3Xurltrmxz/VO21īenrLq3LuVRkn3srn6c8Ov9a7a38hNaphZndfiV6/bVVev2b6jK7NZsSWp80R9QrtwRUPm9yL85tqMvZ KEcxQjF3RczinNyEvIwtqe7xZuk2yXuzM7MEq4BGMpSkdZUuyw6oDCtMaBUs1usPLto5LbJg78圓GfazĭydYzxCI2TI5JOp1T0hUagdIfWozj2dqs2zo9prHbX+q9s4EieU2nPVUa5YMutO2Ien3JOd5VZNPLvo3ĠXsJSE6tecOE6R25fSD2+3WKEfYr1aLZl71PvLBob3bIwoBK0YWpHZMXlk6ZuOjgnO4lJxfVrZy8Mm+9ĮJxzYmBgOB170EEi8o9NenCltbF/pXWpX53dT5/Jvj99FCO2+2rF5QYWJk+LtM5ySuwqZUrsr7gQfa1W Kib7VqboJX5NvVZrkia4AiTmNGF2cFCXbOidtkcRqc25CWsb6nIM6ydXF9RvmJDdyDBnUQvv0ukdoqv5ĮiLWsvVLrnOYOH0NSN+ntSF+qrOvrQaxDy9PCBfbMXs9iO2zRLFt78rUjuK1a3oZRsEoGAU0AQAtjkOVĮJyzZWBgEIpmcfaPEfXniusq5Y09mDcxWjb0QvR3y9OxWgYHEhM0P6UlaK7OfG2QmVVqoZNpb5+Z1ef1 Lu1eYnTAZC3vZZCc8mnrGT8PHZxzZB/HojO7L60I2CW7UXCX1q7zu8wPu+1jOWt8lPdy1gmfSxon3c8zĮJzTYmBgeJUp6BNWeCuouzQ3gbPMKEWweGfG24y92eeLCyd6l9rP5il1nne+2H2heGHX4g3pvEuBWhjq Ih1negr3n+zde7ynx/nMpK6jZ7Ubj54F6a2tet+/qzpguWXN5wNbawOugsT2riydEr6AYc7CORyLEufw Q2/awTN3K4dE1SFBsN4DK14bhO14bQBiv2lY0/uwZUWXcFdmd1dvbt+xPqNJbP07p3n17p35pJljkUD3 L17yAWplOFTxnXt/5WT5/ZUQ/u15nzlWznQX7+pdY+jRV2hqM元P68GcmBCQXNqmQvbnG79zcy096gzi WbPnTVcqmbrBZOfkSmuNWYI+R5cZpYDEF21+HRexvc3FeX+XZPyZAO/w8xD1fLvPeq4/ds2fYRSMgmEOĮJzzYWBg6C2pE7Cr2sFTXGfFl9HkLJLcclY6uUVUcWlzhPLHugRNw/oUHeWWSutFLRxuqc08nltrL/l4 W87J7gtDO9/vDeoqO/RjcsBV2XmPH4HEJy6yn+25dMM+9mXdF88u5l3Ku+TgHK6lVdOPLjObuntV6RTDĭT+mJm8+OOf5xrYFjit4lyZvzt2zaHPhfpXNPw4/32h9bPNa+5MXFjWdBpl1vljLQLA4IVy88元x9YLJĨlcLOSS8S4+KVtR4S62vv6aY2xCjltvwSGt9/XPd/5V6xn+qSi3utU72vdkuGSTRIRv6sEUxYmrhowiQ TNGFJ0suL7zV4LNEq+fw8tIplav3zsxbf3BOxPaDcxhGwSgYBXQDAM2DQRA ĮJzzYGBg+FjHu/RU6clF4oVdi+/nnluqlSW7UStrxY5l2WWHZhScvDChWPDa0fJrN3dVT7/1vSbkBlAL K6513GqQbl/RdafNbOqs9qPzQzv7lzVNm元edKrsxsQ5s9eD1D/feKvh7XrZjWvXc5RobrTPjd52MK9jī0Clw4GI+tZ9ss1hO1Z0iex839+67+Ac5/1H5zft7192ZN/klV17pq+5suPWOvuVEHNGwSgYBbQBAKAdĮJxTZWBgqEyRbDhbEuLXUHmufFe1YhtQiKEkLaI+MTemqbVcsgHEF+7iKBHrXNM7qWtvdk/Pkki2/ukBĭBMv+eyZFOD9eaqgz+sZs4NfzHweXTStMPlkr33uyV6WQttJj9tsJ63oim3T6gGZobMhIbx5eWZs4KKq Ik7BMQaHd8faXL4c8fbo2nMJbMb7+qqjk7pCas51X6vVnVF2CCSm2RSyynbStdUg9tv1K7pOL2lbcHWBĦOodq9W266/X2/t2vdEBkJzdwel1frsftwXsyuwO2GU0qXe3/eym/ddWbzmSuTP3uN7emec+g9Ud2h9QĮJzTZGBg6It5vn1dxuTqxTmFyfJ59rnXC3L7/Er6lwGlGOyTjCYZpf+Y+ihn5zQQf9105wKnCUcL+Xr6 QQdWlKblrT+Yl7bJu0xl86Uq9U23Gt6vS2itXpXaMXlhagfDKBgFo4AuAAAQK0Ge ĮJzTY2BgmBi9M+NylGLbjQiGOXPCP0+SDbfOigl/Hj0t8pp/T2yAN2uCoI9N8jX/nMzUqBdZa+KXZZemĦWRaZ7EmHMzzj3EvPhfjXVaT/LjtV/KGCX+Tdk5zj3eeJxHJu1Q1JGA50HiGgxNkQzfV2ed6lk2u5imVīDhVmtBaXHd0vkff3uMgeZtVRimNK6oyF845uUh3xvu9ILHvq1/H3d+yc9qknbfWce7N3QMSu7qganrhĮJxzZGBguBdWmCwaddKNIz5C+XDCWem/SZIqbzOcnWTy1aKB0gzu8RxurzJPuoHY0u0xat9r9IwbKiutĩ1cyOCi0ZsZGdBQmg+S2TdlgsnHaZN8tUw86bJl6TdFomrt4/nR7Qa2ZVnzz5lrxBS5yFvFf7C7et9hbĦsKiPhn5udcU+xYXmvossbbpW8zgsHBOm8uHae6uILMys3L73OO3TOaNrZp+IfrgnAvR3kuOxadu25b6Ĥ3BKDsOp6wV7j4sX7jwCUnuue0XX2gb72Xur+pf9qZq88lw372WQeOT85537JpYdArEvL5zfcmLpwTk6ĮJyzZ2BgYKz09ljb4Cyi2dQmptziL8vdy+AAFGYorV1jqNyywSSge4MJiH9h0VHRNTO0DLRmbjB5MGevħYVFJ90aVwj6gOTmbg1RkNxuZim5XdR/1rajomI7rPj4dpdyNRz4zl1xeC+/9omz0lknJsvrHZ+tempP Qc23GsQ6X/dw9JVOAclfXcDhNnnhmvjJC1/3iC486nx2MYuz4Toez1cbBH2Wbrrmn7w5JiRzY2qU+7It EJxTY2BgaPWwnpEbaJ97O9zbQzQqxO9DulYPUJhBObS/gikxpOZRzqUqEH/fxJiQ9/V1OcZ1zgXFde7F






Human resource machine year 32