Episode #,Training Iter,In Heatup,ER #Transitions,ER #Episodes,Episode Length,Total steps,Epsilon,Shaped Training Reward,Training Reward,Update Target Network,Evaluation Reward,Shaped Evaluation Reward,Success Rate,Loss/Mean,Loss/Stdev,Loss/Max,Loss/Min,Learning Rate/Mean,Learning Rate/Stdev,Learning Rate/Max,Learning Rate/Min,Grads (unclipped)/Mean,Grads (unclipped)/Stdev,Grads (unclipped)/Max,Grads (unclipped)/Min,Discounted Return/Mean,Discounted Return/Stdev,Discounted Return/Max,Discounted Return/Min,Entropy/Mean,Entropy/Stdev,Entropy/Max,Entropy/Min,Q/Mean,Q/Stdev,Q/Max,Q/Min,Q Values/Mean,Q Values/Stdev,Q Values/Max,Q Values/Min,Value Loss/Mean,Value Loss/Stdev,Value Loss/Max,Value Loss/Min
1,0.0,1.0,486.0,1.0,486.0,486.0,0.5,,,0.0,,,,,,,,,,,,,,,,1.027285241237078,0.8961037725396955,3.502959469093688,0.0,,,,,,,,,,,,,,,,
2,0.0,1.0,87.0,1.0,87.0,573.0,0.5,,,0.0,,,,,,,,,,,,,,,,0.2991949731169189,0.4147830569909918,1.0,0.0,,,,,,,,,,,,,,,,
3,0.0,1.0,149.0,1.0,149.0,722.0,0.5,,,0.0,,,,,,,,,,,,,,,,1.089942054123867,0.6773639260883686,1.9560606270183023,0.0,,,,,,,,,,,,,,,,
4,0.0,1.0,335.0,1.0,335.0,1057.0,0.5,,,0.0,,,,,,,,,,,,,,,,1.6150170189100268,1.2171006279541683,4.3034191502088746,0.0,,,,,,,,,,,,,,,,
5,43.0,0.0,218.0,1.0,218.0,1275.0,0.4978635999999991,4.0,30.0,0.0,,,,,,,,,,,,,,,,1.4355558153956027,0.8743774426398123,3.18289891640664,0.0,,,,,,,,,0.049821895,0.040794298,0.16144831,-0.04194873599999999,0.06658878,0.20887113,0.92870796,1.3539827000000001e-05
6,82.0,0.0,195.0,1.0,195.0,1470.0,0.4959525999999982,2.0,35.0,0.0,,,,,,,,,,,,,,,,0.5266968407467524,0.3693588813641733,1.2762516676992082,0.0,,,,,,,,,0.07430909599999999,0.031378473999999996,0.15561001,0.017140895,0.03804031,0.16481854,0.9850528000000001,0.0002183407
7,131.0,0.0,243.0,1.0,243.0,1713.0,0.4935711999999972,0.0,0.0,0.0,,,,,,,,,,,,,,,,0.0,0.0,0.0,0.0,,,,,,,,,0.04265518,0.020237265,0.12036709,-0.012695962,0.0005867248999999999,0.00071001943,0.004012562,5.224298e-06
8,183.0,0.0,260.0,1.0,260.0,1973.0,0.4910231999999961,6.0,45.0,0.0,,,,,,,,,,,,,,,,1.8445302223733409,0.9773846948142106,3.529722201807415,0.0,,,,,,,,,0.065202,0.0400596,0.21712853,0.0068587554,0.065516554,0.19554858,0.8884774999999999,3.5797817e-05
9,249.0,0.0,329.0,1.0,329.0,2302.0,0.4877989999999947,6.0,100.0,0.0,,,,,,,,,,,,,,,,1.392666868216866,1.0394071747173437,3.6111183571713448,0.0,,,,,,,,,0.056425206,0.037720352,0.16072667,-0.04126611,0.036703362999999996,0.11380449,0.5483772,0.00036559267999999997
10,355.0,0.0,529.0,1.0,529.0,2831.0,0.4826147999999925,4.0,55.0,0.0,,,,,,,,,,,,,,,,0.7058811552247987,0.6338784621102189,2.6758599618307444,0.0,,,,,,,,,0.0295469,0.019959169,0.100820765,-0.019850466,0.026555283,0.14218670000000003,0.95402884,3.3959244e-05
11,382.0,0.0,136.0,1.0,136.0,2967.0,0.4812819999999919,0.0,0.0,0.0,,,,,,,,,,,,,,,,0.0,0.0,0.0,0.0,,,,,,,,,0.070838,0.020381957,0.12719424,0.027900666,0.0011888286999999999,0.0012110863,0.005692898,2.8870036e-05
12,437.0,0.0,272.0,1.0,272.0,3239.0,0.4786163999999907,5.0,75.0,0.0,,,,,,,,,,,,,,,,0.7965494499155914,0.7676873795288424,3.0706061095113872,0.0,,,,,,,,,0.06791638,0.030165499999999998,0.14470898,-0.03135575,0.055119842,0.17865935,0.89836913,0.00041550235
13,526.0,0.0,445.0,1.0,445.0,3684.0,0.4742553999999888,6.0,70.0,0.0,,,,,,,,,,,,,,,,0.9250639900550434,1.3791755980793503,4.6070750958301225,0.0,,,,,,,,,0.05033615599999999,0.04090539,0.21611296,-0.00539122,0.04374561,0.15804026,0.88217527,5.6085350000000005e-06
14,568.0,0.0,211.0,1.0,211.0,3895.0,0.472187599999988,4.0,35.0,0.0,,,,,,,,,,,,,,,,1.3211683635631786,0.6688764763247202,2.6041154043144044,0.0,,,,,,,,,0.06951321,0.026168478999999998,0.1383483,0.017367069,0.037633757999999996,0.12640582,0.7049002,7.566997400000001e-05
15,588.0,0.0,99.0,1.0,99.0,3994.0,0.4712173999999875,1.0,20.0,0.0,,,,,,,,,,,,,,,,0.3275464150906228,0.4105264429665964,1.0,0.0,,,,,,,,,0.061873578,0.027288637999999997,0.11769849,0.006314104,0.039941784,0.16420019,0.7365783,0.0004206792
16,628.0,0.0,197.0,1.0,197.0,4191.0,0.4692867999999867,0.0,0.0,0.0,,,,,,,,,,,,,,,,0.0,0.0,0.0,0.0,,,,,,,,,0.035919555,0.019500284,0.095511,-0.011271331,0.0005676733,0.00042882026,0.0016585776,2.5987260999999998e-05
17,737.0,0.0,543.0,1.0,543.0,4734.0,0.4639653999999844,13.0,230.0,0.0,,,,,,,,,,,,,,,,2.12068282338126,1.613926274284711,4.811923111070045,0.0,,,,,,,,,0.07359602,0.031097147999999998,0.16789229,-0.0072538974,0.055959634,0.15358616,0.7472243000000001,1.1038916999999998e-05
18,770.0,0.0,163.0,1.0,163.0,4897.0,0.4623679999999837,1.0,20.0,0.0,,,,,,,,,,,,,,,,0.3999428745445137,0.3331373421595941,1.0,0.0,,,,,,,,,0.039978374,0.023399489,0.09573812,-0.004045846,0.030746099,0.16456035,0.9469624,0.00016566872
19,813.0,0.0,216.0,1.0,216.0,5113.0,0.4602511999999828,0.0,0.0,0.0,,,,,,,,,,,,,,,,0.0,0.0,0.0,0.0,,,,,,,,,0.041446723,0.015750267,0.08521996,0.0036349134,0.0005720068599999999,0.0005356747,0.0020601498,6.6438793e-06
20,855.0,0.0,207.0,1.0,207.0,5320.0,0.4582225999999819,3.0,30.0,0.0,,,,,,,,,,,,,,,,1.1196867985922996,0.7253527014570459,2.5969380989884208,0.0,,,,,,,,,0.07086054,0.030868992,0.15472650000000002,0.021865197000000003,0.045209922,0.16471039,0.9026728999999999,7.0652815e-05