Run v3
This commit is contained in:
Johnny Fernandes
@@ -0,0 +1,242 @@
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Config loaded from config.json
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Config: {'W_PER_SHEEP': 2.0, 'W_ALIGN': 0.05, 'W_PEN_BONUS': 10.0, 'W_COMPLETE': 100.0, 'W_STEP_COST': 0.02, 'W_SOUTH': 0.01, 'W_COMPACT': 0.0, 'W_WALL_TOUCH': 0.0, 'WALL_TOUCH_BUFFER': 0.4, 'ALIGN_SHAPE': 'standoff', 'ALIGN_GATED': True, 'ENTRY_AWARE': True, 'ent_coef': 0.02}
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Run dir: runs/v3
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Curriculum: 1 → 10 sheep, 1,500,000 steps/stage
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[Stage n_sheep=1] training 1,500,000 steps
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... [1 sheep | 100,000 steps | ret(last 24)=-47.74 win_sr=12% cum_sr=12%]
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... [1 sheep | 200,000 steps | ret(last 50)=-40.77 win_sr=14% cum_sr=16%]
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... [1 sheep | 300,000 steps | ret(last 50)=-36.39 win_sr=16% cum_sr=16%]
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... [1 sheep | 400,000 steps | ret(last 50)=-40.04 win_sr=14% cum_sr=15%]
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... [1 sheep | 500,000 steps | ret(last 50)=+7.09 win_sr=80% cum_sr=36%]
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... [1 sheep | 600,000 steps | ret(last 50)=+15.87 win_sr=100% cum_sr=71%]
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... [1 sheep | 700,000 steps | ret(last 50)=+14.78 win_sr=100% cum_sr=84%]
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... [1 sheep | 800,000 steps | ret(last 50)=+14.04 win_sr=100% cum_sr=90%]
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... [1 sheep | 900,000 steps | ret(last 50)=+14.08 win_sr=100% cum_sr=92%]
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... [1 sheep | 1,000,000 steps | ret(last 50)=+13.33 win_sr=100% cum_sr=94%]
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... [1 sheep | 1,100,000 steps | ret(last 50)=+13.99 win_sr=100% cum_sr=95%]
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... [1 sheep | 1,200,000 steps | ret(last 50)=+13.38 win_sr=100% cum_sr=96%]
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... [1 sheep | 1,300,000 steps | ret(last 50)=+13.18 win_sr=100% cum_sr=96%]
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... [1 sheep | 1,400,000 steps | ret(last 50)=+13.53 win_sr=100% cum_sr=97%]
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... [1 sheep | 1,500,000 steps | ret(last 50)=+13.46 win_sr=100% cum_sr=97%]
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[Stage n_sheep=1] evaluating 30 eps
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[Stage n_sheep=1] sr=100% mean_len=264 mean_min_pen=3.7m mean_act=0.45
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failure modes: SUCCESS=30
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reward/step: progress=+0.1156 alignment=+0.0001 south=-0.0005 compact=+0.0000 wall_touch=+0.0000 pen_bonus=+0.0378 step_cost=-0.0200 complete=+0.3784
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[Stage n_sheep=2] training 1,500,000 steps
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... [2 sheep | 1,507,336 steps | ret(last 0)=+nan win_sr=nan% cum_sr=nan%]
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... [2 sheep | 1,607,336 steps | ret(last 35)=-3.04 win_sr=49% cum_sr=49%]
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... [2 sheep | 1,707,336 steps | ret(last 50)=-11.13 win_sr=20% cum_sr=33%]
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... [2 sheep | 1,807,336 steps | ret(last 50)=-11.83 win_sr=18% cum_sr=31%]
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... [2 sheep | 1,907,336 steps | ret(last 50)=-8.76 win_sr=30% cum_sr=31%]
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... [2 sheep | 2,007,336 steps | ret(last 50)=-8.95 win_sr=30% cum_sr=30%]
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... [2 sheep | 2,107,336 steps | ret(last 50)=-9.06 win_sr=32% cum_sr=30%]
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... [2 sheep | 2,207,336 steps | ret(last 50)=-9.48 win_sr=32% cum_sr=30%]
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... [2 sheep | 2,307,336 steps | ret(last 50)=-1.70 win_sr=44% cum_sr=33%]
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... [2 sheep | 2,407,336 steps | ret(last 50)=+5.02 win_sr=64% cum_sr=38%]
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... [2 sheep | 2,507,336 steps | ret(last 50)=+13.32 win_sr=88% cum_sr=46%]
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... [2 sheep | 2,607,336 steps | ret(last 50)=+12.15 win_sr=90% cum_sr=54%]
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... [2 sheep | 2,707,336 steps | ret(last 50)=+17.13 win_sr=98% cum_sr=63%]
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... [2 sheep | 2,807,336 steps | ret(last 50)=+18.81 win_sr=98% cum_sr=69%]
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... [2 sheep | 2,907,336 steps | ret(last 50)=+16.23 win_sr=92% cum_sr=73%]
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... [2 sheep | 3,007,336 steps | ret(last 50)=+18.83 win_sr=100% cum_sr=76%]
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[Stage n_sheep=2] evaluating 30 eps
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[Stage n_sheep=2] sr=77% mean_len=1398 mean_min_pen=3.3m mean_act=0.97
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failure modes: SUCCESS=23 PARTIAL_1of2=6 COMPACT_CANT_DRIVE=1
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reward/step: progress=+0.0401 alignment=+0.0045 south=-0.0039 compact=+0.0000 wall_touch=+0.0000 pen_bonus=+0.0126 step_cost=-0.0200 complete=+0.0549
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[Stage n_sheep=3] training 1,500,000 steps
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... [3 sheep | 3,014,664 steps | ret(last 0)=+nan win_sr=nan% cum_sr=nan%]
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... [3 sheep | 3,114,664 steps | ret(last 50)=+13.79 win_sr=82% cum_sr=84%]
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... [3 sheep | 3,214,664 steps | ret(last 50)=+21.64 win_sr=96% cum_sr=88%]
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... [3 sheep | 3,314,664 steps | ret(last 50)=+23.45 win_sr=98% cum_sr=92%]
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... [3 sheep | 3,414,664 steps | ret(last 50)=+22.18 win_sr=98% cum_sr=94%]
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... [3 sheep | 3,514,664 steps | ret(last 50)=+24.83 win_sr=100% cum_sr=96%]
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... [3 sheep | 3,614,664 steps | ret(last 50)=+19.77 win_sr=94% cum_sr=96%]
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... [3 sheep | 3,714,664 steps | ret(last 50)=+25.53 win_sr=100% cum_sr=96%]
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... [3 sheep | 3,814,664 steps | ret(last 50)=+25.24 win_sr=100% cum_sr=97%]
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... [3 sheep | 3,914,664 steps | ret(last 50)=+24.43 win_sr=100% cum_sr=97%]
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... [3 sheep | 4,014,664 steps | ret(last 50)=+24.59 win_sr=100% cum_sr=97%]
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... [3 sheep | 4,114,664 steps | ret(last 50)=+22.18 win_sr=98% cum_sr=98%]
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... [3 sheep | 4,214,664 steps | ret(last 50)=+23.11 win_sr=96% cum_sr=97%]
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... [3 sheep | 4,314,664 steps | ret(last 50)=+23.06 win_sr=98% cum_sr=97%]
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... [3 sheep | 4,414,664 steps | ret(last 50)=+23.35 win_sr=100% cum_sr=97%]
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... [3 sheep | 4,514,664 steps | ret(last 50)=+22.50 win_sr=100% cum_sr=98%]
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[Stage n_sheep=3] evaluating 30 eps
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[Stage n_sheep=3] sr=97% mean_len=1095 mean_min_pen=2.5m mean_act=0.95
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failure modes: SUCCESS=29 COMPACT_CANT_DRIVE=1
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reward/step: progress=+0.0821 alignment=+0.0113 south=-0.0087 compact=+0.0000 wall_touch=+0.0000 pen_bonus=+0.0265 step_cost=-0.0200 complete=+0.0883
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[Stage n_sheep=4] training 1,500,000 steps
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... [4 sheep | 4,521,992 steps | ret(last 0)=+nan win_sr=nan% cum_sr=nan%]
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... [4 sheep | 4,621,992 steps | ret(last 50)=+22.17 win_sr=92% cum_sr=94%]
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... [4 sheep | 4,721,992 steps | ret(last 50)=+25.81 win_sr=94% cum_sr=93%]
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... [4 sheep | 4,821,992 steps | ret(last 50)=+21.80 win_sr=90% cum_sr=93%]
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... [4 sheep | 4,921,992 steps | ret(last 50)=+26.38 win_sr=98% cum_sr=94%]
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... [4 sheep | 5,021,992 steps | ret(last 50)=+26.65 win_sr=98% cum_sr=95%]
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... [4 sheep | 5,121,992 steps | ret(last 50)=+26.07 win_sr=98% cum_sr=95%]
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... [4 sheep | 5,221,992 steps | ret(last 50)=+27.08 win_sr=98% cum_sr=96%]
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... [4 sheep | 5,321,992 steps | ret(last 50)=+27.87 win_sr=100% cum_sr=96%]
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... [4 sheep | 5,421,992 steps | ret(last 50)=+27.53 win_sr=100% cum_sr=97%]
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... [4 sheep | 5,521,992 steps | ret(last 50)=+25.91 win_sr=100% cum_sr=97%]
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... [4 sheep | 5,621,992 steps | ret(last 50)=+27.75 win_sr=100% cum_sr=97%]
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... [4 sheep | 5,721,992 steps | ret(last 50)=+25.63 win_sr=100% cum_sr=97%]
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... [4 sheep | 5,821,992 steps | ret(last 50)=+24.43 win_sr=98% cum_sr=97%]
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... [4 sheep | 5,921,992 steps | ret(last 50)=+22.52 win_sr=94% cum_sr=97%]
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... [4 sheep | 6,021,992 steps | ret(last 50)=+27.28 win_sr=100% cum_sr=98%]
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[Stage n_sheep=4] evaluating 30 eps
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[Stage n_sheep=4] sr=57% mean_len=2572 mean_min_pen=2.2m mean_act=1.28
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failure modes: SUCCESS=17 PARTIAL_1of4=6 PARTIAL_2of4=5 DROVE_NO_SHEEP=1 NEVER_COMPACT=1
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reward/step: progress=+0.0455 alignment=+0.0040 south=-0.0454 compact=+0.0000 wall_touch=+0.0000 pen_bonus=+0.0109 step_cost=-0.0200 complete=+0.0220
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[Stage n_sheep=5] training 1,500,000 steps
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... [5 sheep | 6,029,320 steps | ret(last 0)=+nan win_sr=nan% cum_sr=nan%]
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... [5 sheep | 6,129,320 steps | ret(last 50)=+28.06 win_sr=96% cum_sr=96%]
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... [5 sheep | 6,229,320 steps | ret(last 50)=+31.40 win_sr=98% cum_sr=96%]
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... [5 sheep | 6,329,320 steps | ret(last 50)=+27.81 win_sr=96% cum_sr=96%]
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... [5 sheep | 6,429,320 steps | ret(last 50)=+22.08 win_sr=88% cum_sr=95%]
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... [5 sheep | 6,529,320 steps | ret(last 50)=+26.99 win_sr=94% cum_sr=95%]
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... [5 sheep | 6,629,320 steps | ret(last 50)=+21.24 win_sr=86% cum_sr=93%]
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... [5 sheep | 6,729,320 steps | ret(last 50)=+24.58 win_sr=94% cum_sr=93%]
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... [5 sheep | 6,829,320 steps | ret(last 50)=+29.66 win_sr=96% cum_sr=93%]
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... [5 sheep | 6,929,320 steps | ret(last 50)=+27.53 win_sr=96% cum_sr=93%]
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... [5 sheep | 7,029,320 steps | ret(last 50)=+28.99 win_sr=100% cum_sr=94%]
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... [5 sheep | 7,129,320 steps | ret(last 50)=+27.59 win_sr=98% cum_sr=94%]
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... [5 sheep | 7,229,320 steps | ret(last 50)=+30.79 win_sr=100% cum_sr=95%]
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... [5 sheep | 7,329,320 steps | ret(last 50)=+30.56 win_sr=98% cum_sr=95%]
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... [5 sheep | 7,429,320 steps | ret(last 50)=+31.55 win_sr=100% cum_sr=95%]
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... [5 sheep | 7,529,320 steps | ret(last 50)=+29.95 win_sr=100% cum_sr=96%]
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[Stage n_sheep=5] evaluating 30 eps
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[Stage n_sheep=5] sr=0% mean_len=4000 mean_min_pen=1.7m mean_act=1.36
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failure modes: PARTIAL_4of5=17 PARTIAL_1of5=9 PARTIAL_3of5=2 PARTIAL_2of5=2
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reward/step: progress=+0.0396 alignment=+0.0034 south=-0.0393 compact=+0.0000 wall_touch=+0.0000 pen_bonus=+0.0073 step_cost=-0.0200 complete=+0.0000
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[Stage n_sheep=6] training 1,500,000 steps
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... [6 sheep | 7,536,648 steps | ret(last 0)=+nan win_sr=nan% cum_sr=nan%]
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... [6 sheep | 7,636,648 steps | ret(last 50)=+34.50 win_sr=100% cum_sr=100%]
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... [6 sheep | 7,736,648 steps | ret(last 50)=+31.01 win_sr=100% cum_sr=100%]
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... [6 sheep | 7,836,648 steps | ret(last 50)=+33.27 win_sr=100% cum_sr=100%]
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... [6 sheep | 7,936,648 steps | ret(last 50)=+34.81 win_sr=100% cum_sr=100%]
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... [6 sheep | 8,036,648 steps | ret(last 50)=+32.69 win_sr=100% cum_sr=100%]
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... [6 sheep | 8,136,648 steps | ret(last 50)=+31.36 win_sr=96% cum_sr=99%]
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... [6 sheep | 8,236,648 steps | ret(last 50)=+33.71 win_sr=100% cum_sr=99%]
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... [6 sheep | 8,336,648 steps | ret(last 50)=+34.71 win_sr=100% cum_sr=99%]
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... [6 sheep | 8,436,648 steps | ret(last 50)=+31.89 win_sr=96% cum_sr=99%]
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... [6 sheep | 8,536,648 steps | ret(last 50)=+35.63 win_sr=100% cum_sr=99%]
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... [6 sheep | 8,636,648 steps | ret(last 50)=+35.92 win_sr=100% cum_sr=99%]
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... [6 sheep | 8,736,648 steps | ret(last 50)=+33.70 win_sr=100% cum_sr=99%]
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... [6 sheep | 8,836,648 steps | ret(last 50)=+33.46 win_sr=100% cum_sr=99%]
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... [6 sheep | 8,936,648 steps | ret(last 50)=+35.12 win_sr=100% cum_sr=99%]
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... [6 sheep | 9,036,648 steps | ret(last 50)=+34.21 win_sr=100% cum_sr=100%]
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[Stage n_sheep=6] evaluating 30 eps
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[Stage n_sheep=6] sr=37% mean_len=3137 mean_min_pen=1.8m mean_act=1.37
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failure modes: PARTIAL_4of6=14 SUCCESS=11 PARTIAL_3of6=5
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reward/step: progress=+0.0654 alignment=+0.0085 south=-0.0392 compact=+0.0000 wall_touch=+0.0000 pen_bonus=+0.0146 step_cost=-0.0200 complete=+0.0117
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[Stage n_sheep=7] training 1,500,000 steps
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... [7 sheep | 9,043,976 steps | ret(last 0)=+nan win_sr=nan% cum_sr=nan%]
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... [7 sheep | 9,143,976 steps | ret(last 50)=+36.14 win_sr=100% cum_sr=100%]
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... [7 sheep | 9,243,976 steps | ret(last 50)=+33.77 win_sr=98% cum_sr=99%]
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... [7 sheep | 9,343,976 steps | ret(last 50)=+37.14 win_sr=100% cum_sr=100%]
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... [7 sheep | 9,443,976 steps | ret(last 50)=+39.90 win_sr=100% cum_sr=100%]
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... [7 sheep | 9,543,976 steps | ret(last 50)=+37.52 win_sr=100% cum_sr=100%]
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... [7 sheep | 9,643,976 steps | ret(last 50)=+37.31 win_sr=100% cum_sr=100%]
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... [7 sheep | 9,743,976 steps | ret(last 50)=+36.24 win_sr=100% cum_sr=100%]
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... [7 sheep | 9,843,976 steps | ret(last 50)=+39.67 win_sr=100% cum_sr=100%]
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... [7 sheep | 9,943,976 steps | ret(last 50)=+39.12 win_sr=100% cum_sr=100%]
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... [7 sheep | 10,043,976 steps | ret(last 50)=+37.82 win_sr=100% cum_sr=100%]
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... [7 sheep | 10,143,976 steps | ret(last 50)=+37.38 win_sr=100% cum_sr=100%]
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... [7 sheep | 10,243,976 steps | ret(last 50)=+37.47 win_sr=98% cum_sr=100%]
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... [7 sheep | 10,343,976 steps | ret(last 50)=+36.04 win_sr=98% cum_sr=99%]
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... [7 sheep | 10,443,976 steps | ret(last 50)=+31.71 win_sr=98% cum_sr=99%]
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... [7 sheep | 10,543,976 steps | ret(last 50)=+32.50 win_sr=96% cum_sr=99%]
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[Stage n_sheep=7] evaluating 30 eps
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[Stage n_sheep=7] sr=0% mean_len=4000 mean_min_pen=1.8m mean_act=1.38
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failure modes: PARTIAL_5of7=18 PARTIAL_6of7=7 PARTIAL_3of7=3 PARTIAL_4of7=2
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reward/step: progress=+0.0533 alignment=+0.0069 south=-0.0356 compact=+0.0000 wall_touch=+0.0000 pen_bonus=+0.0124 step_cost=-0.0200 complete=+0.0000
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[Stage n_sheep=8] training 1,500,000 steps
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... [8 sheep | 10,551,304 steps | ret(last 0)=+nan win_sr=nan% cum_sr=nan%]
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... [8 sheep | 10,651,304 steps | ret(last 50)=+36.01 win_sr=96% cum_sr=96%]
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... [8 sheep | 10,751,304 steps | ret(last 50)=+37.97 win_sr=96% cum_sr=96%]
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... [8 sheep | 10,851,304 steps | ret(last 50)=+39.12 win_sr=100% cum_sr=98%]
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... [8 sheep | 10,951,304 steps | ret(last 50)=+36.54 win_sr=96% cum_sr=97%]
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... [8 sheep | 11,051,304 steps | ret(last 50)=+40.58 win_sr=100% cum_sr=98%]
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... [8 sheep | 11,151,304 steps | ret(last 50)=+39.00 win_sr=98% cum_sr=98%]
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... [8 sheep | 11,251,304 steps | ret(last 50)=+38.54 win_sr=98% cum_sr=98%]
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... [8 sheep | 11,351,304 steps | ret(last 50)=+39.29 win_sr=100% cum_sr=98%]
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... [8 sheep | 11,451,304 steps | ret(last 50)=+38.36 win_sr=100% cum_sr=98%]
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... [8 sheep | 11,551,304 steps | ret(last 50)=+40.04 win_sr=100% cum_sr=98%]
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... [8 sheep | 11,651,304 steps | ret(last 50)=+37.92 win_sr=100% cum_sr=99%]
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... [8 sheep | 11,751,304 steps | ret(last 50)=+40.01 win_sr=98% cum_sr=99%]
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... [8 sheep | 11,851,304 steps | ret(last 50)=+39.06 win_sr=100% cum_sr=99%]
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... [8 sheep | 11,951,304 steps | ret(last 50)=+41.39 win_sr=100% cum_sr=99%]
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... [8 sheep | 12,051,304 steps | ret(last 50)=+40.05 win_sr=100% cum_sr=99%]
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[Stage n_sheep=8] evaluating 30 eps
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[Stage n_sheep=8] sr=60% mean_len=2472 mean_min_pen=1.6m mean_act=1.39
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failure modes: SUCCESS=18 PARTIAL_6of8=9 PARTIAL_4of8=3
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reward/step: progress=+0.0956 alignment=+0.0106 south=-0.0508 compact=+0.0000 wall_touch=+0.0000 pen_bonus=+0.0283 step_cost=-0.0200 complete=+0.0243
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[Stage n_sheep=9] training 1,500,000 steps
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... [9 sheep | 12,058,632 steps | ret(last 0)=+nan win_sr=nan% cum_sr=nan%]
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... [9 sheep | 12,158,632 steps | ret(last 50)=+41.35 win_sr=98% cum_sr=98%]
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... [9 sheep | 12,258,632 steps | ret(last 50)=+41.63 win_sr=100% cum_sr=99%]
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... [9 sheep | 12,358,632 steps | ret(last 50)=+41.85 win_sr=100% cum_sr=99%]
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... [9 sheep | 12,458,632 steps | ret(last 50)=+42.49 win_sr=100% cum_sr=100%]
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... [9 sheep | 12,558,632 steps | ret(last 50)=+40.87 win_sr=100% cum_sr=100%]
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... [9 sheep | 12,658,632 steps | ret(last 50)=+39.09 win_sr=100% cum_sr=100%]
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... [9 sheep | 12,758,632 steps | ret(last 50)=+42.23 win_sr=100% cum_sr=100%]
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... [9 sheep | 12,858,632 steps | ret(last 50)=+41.00 win_sr=100% cum_sr=100%]
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... [9 sheep | 12,958,632 steps | ret(last 50)=+43.02 win_sr=100% cum_sr=100%]
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... [9 sheep | 13,058,632 steps | ret(last 50)=+41.13 win_sr=100% cum_sr=100%]
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... [9 sheep | 13,158,632 steps | ret(last 50)=+41.02 win_sr=100% cum_sr=100%]
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... [9 sheep | 13,258,632 steps | ret(last 50)=+42.88 win_sr=100% cum_sr=100%]
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... [9 sheep | 13,358,632 steps | ret(last 50)=+46.16 win_sr=100% cum_sr=100%]
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... [9 sheep | 13,458,632 steps | ret(last 50)=+44.69 win_sr=100% cum_sr=100%]
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... [9 sheep | 13,558,632 steps | ret(last 50)=+44.49 win_sr=100% cum_sr=100%]
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[Stage n_sheep=9] evaluating 30 eps
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[Stage n_sheep=9] sr=0% mean_len=4000 mean_min_pen=1.5m mean_act=1.39
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failure modes: PARTIAL_8of9=26 PARTIAL_7of9=4
|
||||
reward/step: progress=+0.0787 alignment=+0.0079 south=-0.0184 compact=+0.0000 wall_touch=+0.0000 pen_bonus=+0.0197 step_cost=-0.0200 complete=+0.0000
|
||||
|
||||
[Stage n_sheep=10] training 1,500,000 steps
|
||||
... [10 sheep | 13,565,960 steps | ret(last 0)=+nan win_sr=nan% cum_sr=nan%]
|
||||
... [10 sheep | 13,665,960 steps | ret(last 50)=+43.38 win_sr=100% cum_sr=100%]
|
||||
... [10 sheep | 13,765,960 steps | ret(last 50)=+43.26 win_sr=100% cum_sr=100%]
|
||||
... [10 sheep | 13,865,960 steps | ret(last 50)=+46.91 win_sr=100% cum_sr=100%]
|
||||
... [10 sheep | 13,965,960 steps | ret(last 50)=+45.36 win_sr=100% cum_sr=100%]
|
||||
... [10 sheep | 14,065,960 steps | ret(last 50)=+45.37 win_sr=100% cum_sr=100%]
|
||||
... [10 sheep | 14,165,960 steps | ret(last 50)=+44.30 win_sr=100% cum_sr=100%]
|
||||
... [10 sheep | 14,265,960 steps | ret(last 50)=+43.83 win_sr=100% cum_sr=100%]
|
||||
... [10 sheep | 14,365,960 steps | ret(last 50)=+47.09 win_sr=100% cum_sr=100%]
|
||||
... [10 sheep | 14,465,960 steps | ret(last 50)=+41.32 win_sr=100% cum_sr=100%]
|
||||
... [10 sheep | 14,565,960 steps | ret(last 50)=+45.30 win_sr=100% cum_sr=100%]
|
||||
... [10 sheep | 14,665,960 steps | ret(last 50)=+45.36 win_sr=98% cum_sr=100%]
|
||||
... [10 sheep | 14,765,960 steps | ret(last 50)=+41.83 win_sr=100% cum_sr=100%]
|
||||
... [10 sheep | 14,865,960 steps | ret(last 50)=+44.40 win_sr=100% cum_sr=100%]
|
||||
... [10 sheep | 14,965,960 steps | ret(last 50)=+45.89 win_sr=100% cum_sr=100%]
|
||||
... [10 sheep | 15,065,960 steps | ret(last 50)=+42.49 win_sr=100% cum_sr=100%]
|
||||
[Stage n_sheep=10] evaluating 30 eps
|
||||
[Stage n_sheep=10] sr=83% mean_len=2243 mean_min_pen=1.5m mean_act=1.40
|
||||
failure modes: SUCCESS=25 PARTIAL_8of10=3 PARTIAL_7of10=2
|
||||
reward/step: progress=+0.1387 alignment=+0.0150 south=-0.0437 compact=+0.0000 wall_touch=+0.0000 pen_bonus=+0.0428 step_cost=-0.0200 complete=+0.0372
|
||||
|
||||
======================================================================
|
||||
TRAINING SUMMARY
|
||||
======================================================================
|
||||
n_sheep=1 sr=100% len= 264 min_pen= 3.7m act=0.45
|
||||
n_sheep=2 sr= 77% len= 1398 min_pen= 3.3m act=0.97
|
||||
n_sheep=3 sr= 97% len= 1095 min_pen= 2.5m act=0.95
|
||||
n_sheep=4 sr= 57% len= 2572 min_pen= 2.2m act=1.28
|
||||
n_sheep=5 sr= 0% len= 4000 min_pen= 1.7m act=1.36
|
||||
n_sheep=6 sr= 37% len= 3137 min_pen= 1.8m act=1.37
|
||||
n_sheep=7 sr= 0% len= 4000 min_pen= 1.8m act=1.38
|
||||
n_sheep=8 sr= 60% len= 2472 min_pen= 1.6m act=1.39
|
||||
n_sheep=9 sr= 0% len= 4000 min_pen= 1.5m act=1.39
|
||||
n_sheep=10 sr= 83% len= 2243 min_pen= 1.5m act=1.40
|
||||
|
||||
Total time: 94.3 min
|
||||
Artefacts: runs/v3/
|
||||
Plots: runs/v3/success_rate.png, runs/v3/eval/
|
||||
@@ -0,0 +1,15 @@
|
||||
{
|
||||
"W_PER_SHEEP": 2.0,
|
||||
"W_ALIGN": 0.05,
|
||||
"W_PEN_BONUS": 10.0,
|
||||
"W_COMPLETE": 100.0,
|
||||
"W_STEP_COST": 0.02,
|
||||
"W_SOUTH": 0.01,
|
||||
"W_COMPACT": 0.0,
|
||||
"W_WALL_TOUCH": 0.0,
|
||||
"WALL_TOUCH_BUFFER": 0.4,
|
||||
"ALIGN_SHAPE": "standoff",
|
||||
"ALIGN_GATED": true,
|
||||
"ENTRY_AWARE": true,
|
||||
"ent_coef": 0.02
|
||||
}
|
||||
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|
||||
[
|
||||
{
|
||||
"sr": 1.0,
|
||||
"mean_len": 264.3,
|
||||
"mean_min_pen": 3.6947483142217,
|
||||
"mean_act": 0.4488927691353647,
|
||||
"failure_modes": {
|
||||
"SUCCESS": 30
|
||||
},
|
||||
"reward_per_step": {
|
||||
"progress": 0.11562251145796992,
|
||||
"alignment": 0.00012847888517811197,
|
||||
"south": -0.00046327802870008703,
|
||||
"compact": 0.0,
|
||||
"wall_touch": 0.0,
|
||||
"pen_bonus": 0.037835792659856225,
|
||||
"step_cost": -0.020000000000000923,
|
||||
"complete": 0.37835792659856227
|
||||
},
|
||||
"n_sheep": 1
|
||||
},
|
||||
{
|
||||
"sr": 0.7666666666666667,
|
||||
"mean_len": 1397.6333333333334,
|
||||
"mean_min_pen": 3.3354002753893535,
|
||||
"mean_act": 0.9679237489606706,
|
||||
"failure_modes": {
|
||||
"SUCCESS": 23,
|
||||
"PARTIAL_1of2": 6,
|
||||
"COMPACT_CANT_DRIVE": 1
|
||||
},
|
||||
"reward_per_step": {
|
||||
"progress": 0.04012407340533507,
|
||||
"alignment": 0.004549029322963513,
|
||||
"south": -0.003855391958439705,
|
||||
"compact": 0.0,
|
||||
"wall_touch": 0.0,
|
||||
"pen_bonus": 0.01264041594123399,
|
||||
"step_cost": -0.019999999999988728,
|
||||
"complete": 0.05485463521667581
|
||||
},
|
||||
"n_sheep": 2
|
||||
},
|
||||
{
|
||||
"sr": 0.9666666666666667,
|
||||
"mean_len": 1095.3666666666666,
|
||||
"mean_min_pen": 2.4724439779917398,
|
||||
"mean_act": 0.950618689999602,
|
||||
"failure_modes": {
|
||||
"SUCCESS": 29,
|
||||
"COMPACT_CANT_DRIVE": 1
|
||||
},
|
||||
"reward_per_step": {
|
||||
"progress": 0.08207998032411863,
|
||||
"alignment": 0.011342550088712133,
|
||||
"south": -0.008689572376747992,
|
||||
"compact": 0.0,
|
||||
"wall_touch": 0.0,
|
||||
"pen_bonus": 0.0264751529168315,
|
||||
"step_cost": -0.019999999999990636,
|
||||
"complete": 0.08825050972277168
|
||||
},
|
||||
"n_sheep": 3
|
||||
},
|
||||
{
|
||||
"sr": 0.5666666666666667,
|
||||
"mean_len": 2571.866666666667,
|
||||
"mean_min_pen": 2.1761705835660297,
|
||||
"mean_act": 1.2794624905502197,
|
||||
"failure_modes": {
|
||||
"PARTIAL_2of4": 5,
|
||||
"SUCCESS": 17,
|
||||
"DROVE_NO_SHEEP": 1,
|
||||
"NEVER_COMPACT": 1,
|
||||
"PARTIAL_1of4": 6
|
||||
},
|
||||
"reward_per_step": {
|
||||
"progress": 0.04547638401556759,
|
||||
"alignment": 0.003989776116242459,
|
||||
"south": -0.04544084245355691,
|
||||
"compact": 0.0,
|
||||
"wall_touch": 0.0,
|
||||
"pen_bonus": 0.010887034060863705,
|
||||
"step_cost": -0.01999999999998557,
|
||||
"complete": 0.02203328321841464
|
||||
},
|
||||
"n_sheep": 4
|
||||
},
|
||||
{
|
||||
"sr": 0.0,
|
||||
"mean_len": 4000.0,
|
||||
"mean_min_pen": 1.7023075381914774,
|
||||
"mean_act": 1.3590981605617019,
|
||||
"failure_modes": {
|
||||
"PARTIAL_1of5": 9,
|
||||
"PARTIAL_3of5": 2,
|
||||
"PARTIAL_2of5": 2,
|
||||
"PARTIAL_4of5": 17
|
||||
},
|
||||
"reward_per_step": {
|
||||
"progress": 0.039584031492471694,
|
||||
"alignment": 0.003391631218188155,
|
||||
"south": -0.03930825256315925,
|
||||
"compact": 0.0,
|
||||
"wall_touch": 0.0,
|
||||
"pen_bonus": 0.00725,
|
||||
"step_cost": -0.01999999999998423,
|
||||
"complete": 0.0
|
||||
},
|
||||
"n_sheep": 5
|
||||
},
|
||||
{
|
||||
"sr": 0.36666666666666664,
|
||||
"mean_len": 3136.766666666667,
|
||||
"mean_min_pen": 1.7896055857340494,
|
||||
"mean_act": 1.3694271957435262,
|
||||
"failure_modes": {
|
||||
"SUCCESS": 11,
|
||||
"PARTIAL_3of6": 5,
|
||||
"PARTIAL_4of6": 14
|
||||
},
|
||||
"reward_per_step": {
|
||||
"progress": 0.06539200159542725,
|
||||
"alignment": 0.00849681660918308,
|
||||
"south": -0.03917853851677538,
|
||||
"compact": 0.0,
|
||||
"wall_touch": 0.0,
|
||||
"pen_bonus": 0.014558515669000988,
|
||||
"step_cost": -0.019999999999984894,
|
||||
"complete": 0.011689319150292764
|
||||
},
|
||||
"n_sheep": 6
|
||||
},
|
||||
{
|
||||
"sr": 0.0,
|
||||
"mean_len": 4000.0,
|
||||
"mean_min_pen": 1.8426543315251669,
|
||||
"mean_act": 1.383490810132896,
|
||||
"failure_modes": {
|
||||
"PARTIAL_5of7": 18,
|
||||
"PARTIAL_3of7": 3,
|
||||
"PARTIAL_6of7": 7,
|
||||
"PARTIAL_4of7": 2
|
||||
},
|
||||
"reward_per_step": {
|
||||
"progress": 0.05331589305400848,
|
||||
"alignment": 0.00686667034524816,
|
||||
"south": -0.03559404498259062,
|
||||
"compact": 0.0,
|
||||
"wall_touch": 0.0,
|
||||
"pen_bonus": 0.012416666666666666,
|
||||
"step_cost": -0.01999999999998423,
|
||||
"complete": 0.0
|
||||
},
|
||||
"n_sheep": 7
|
||||
},
|
||||
{
|
||||
"sr": 0.6,
|
||||
"mean_len": 2472.0666666666666,
|
||||
"mean_min_pen": 1.609976100921631,
|
||||
"mean_act": 1.3901071324053385,
|
||||
"failure_modes": {
|
||||
"SUCCESS": 18,
|
||||
"PARTIAL_4of8": 3,
|
||||
"PARTIAL_6of8": 9
|
||||
},
|
||||
"reward_per_step": {
|
||||
"progress": 0.09555249268374479,
|
||||
"alignment": 0.010622170754243947,
|
||||
"south": -0.050827120587952045,
|
||||
"compact": 0.0,
|
||||
"wall_touch": 0.0,
|
||||
"pen_bonus": 0.028316388446913515,
|
||||
"step_cost": -0.019999999999985724,
|
||||
"complete": 0.024271190097354442
|
||||
},
|
||||
"n_sheep": 8
|
||||
},
|
||||
{
|
||||
"sr": 0.0,
|
||||
"mean_len": 4000.0,
|
||||
"mean_min_pen": 1.5165573159853618,
|
||||
"mean_act": 1.3936255563423037,
|
||||
"failure_modes": {
|
||||
"PARTIAL_8of9": 26,
|
||||
"PARTIAL_7of9": 4
|
||||
},
|
||||
"reward_per_step": {
|
||||
"progress": 0.07870613823334376,
|
||||
"alignment": 0.007913931652916581,
|
||||
"south": -0.01837508026464782,
|
||||
"compact": 0.0,
|
||||
"wall_touch": 0.0,
|
||||
"pen_bonus": 0.019666666666666666,
|
||||
"step_cost": -0.01999999999998423,
|
||||
"complete": 0.0
|
||||
},
|
||||
"n_sheep": 9
|
||||
},
|
||||
{
|
||||
"sr": 0.8333333333333334,
|
||||
"mean_len": 2243.0,
|
||||
"mean_min_pen": 1.5175361116727193,
|
||||
"mean_act": 1.3979439154633806,
|
||||
"failure_modes": {
|
||||
"SUCCESS": 25,
|
||||
"PARTIAL_7of10": 2,
|
||||
"PARTIAL_8of10": 3
|
||||
},
|
||||
"reward_per_step": {
|
||||
"progress": 0.13872242361851903,
|
||||
"alignment": 0.015031396471697371,
|
||||
"south": -0.04365405077614671,
|
||||
"compact": 0.0,
|
||||
"wall_touch": 0.0,
|
||||
"pen_bonus": 0.04279982166740972,
|
||||
"step_cost": -0.019999999999986123,
|
||||
"complete": 0.03715262297518205
|
||||
},
|
||||
"n_sheep": 10
|
||||
}
|
||||
]
|
||||
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|
After Width: | Height: | Size: 32 KiB |
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Reference in New Issue
Block a user