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,Q/Mean,Q/Stdev,Q/Max,Q/Min
1,0.0,1.0,986.0,986.0,986.0,986.0,7.0,,,0.0,,,,,,,,,,,,,,,,,,,
2,0.0,1.0,1806.0,1806.0,820.0,1806.0,4.0,,,0.0,,,,,,,,,,,,,,,,,,,
3,206.0,0.0,2629.0,2629.0,823.0,2629.0,5.0,-21.0,-21.0,0.0,,,,0.01375627432677452,0.013505330839893808,0.06677445024251938,0.0005553220980800688,0.0002500000000000001,1.0842021724855042e-19,0.00025,0.00025,0.013602738,0.0048916726,0.034245104,0.0056978124,,,,
4,398.0,0.0,3397.0,3397.0,768.0,3397.0,3.0,-21.0,-21.0,0.0,,,,0.014156610367839068,0.013173363350960334,0.059119727462530136,0.0007080046343617141,0.0002500000000000001,5.421010862427521e-20,0.00025,0.00025,0.012839798999999999,0.0038416919,0.024480136,0.005681609000000001,,,,
5,617.0,0.0,4274.0,4274.0,877.0,4274.0,6.0,-21.0,-21.0,0.0,,,,0.015369139484674181,0.01463229484329247,0.08113615959882736,0.0005487628513947129,0.0002500000000000001,1.0842021724855042e-19,0.00025,0.00025,0.014249632,0.005901839599999999,0.04092761,0.004881437,0.004008428,0.016476048,0.028364737,-0.026583625