Now keep the same training settings, except switch the epsilon strategy to Decay. Keep start and minimum epsilon at 1 and 0.05 respectively. Save the policy as Non-Slippery Decay.

When you now train the agent, what is the difference between the greedy heatmap and the decay heatmap here? 

Also, how does the agent behave when you let him tackle the environment (agent playback)? Compare this to the behavior of the greedy agent when you do the agent playback.

Attach the q-table heatmap plot of both agents here as well.