## 4 Results
### Variation of the Exploration Strategy  
As a final step, the exploration strategy of the agent has been varied according to the strategies shown in Section 2.3. Any of the considered exploration strategies are featured by a linear decay of the exploration rate followed or preceded by a constant trace. Specifically, \"boost\" and \"slow\" are characterized by two decays with different slopes followed by a horizontal phase with \(\varepsilon=0.05\). On the contrary, a horizontal phase with \(\varepsilon=0.8\) is maintained for the majority of the experiment and then followed by the linear decrease in \"inverse slow\". The three exploration strategies will be hereafter referred to as L1, L2 and L3, respectively. Different from the results shown in the previous sections, a clear trend is highlighted by the results reported in Table 7 considering the entire set of DMs. In fact, L1 appears to be the best performing exploration strategy as it allows the agent to solve any environment (i.e., complete the missions) while minimizing the FC. L2 and L3 are capable of producing more accurate CS trajectories as the final battery _SoCs_ are comparable with those obtained with DP. Nevertheless, the rFC values are worsened with respect to those achieved with L1. Moreover, the velocity trajectory of CLUST3 cannot be fulfilled as both L2 and L3 are not capable of completing the driving missions without falling outside of the battery _SoC_ window (0.55-0.65). \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**DM**} & \multicolumn{6}{c}{_SoC\({}_{f}\) (\(\star\))_} & \multicolumn{6}{c}{**FC (g)**} \\ \cline{2-9}  & **DP** & **Q1** & **Q1** & **Q1** & **Q1** & **Q1** & **Q1** & **Q1** \\  & & **\(\alpha\) = 0.1** & **\(\alpha\) = 0.5** & **\(\alpha\) = 0.9** & **DP** & **\(\alpha\) = 0.1** & **\(\alpha\) = 0.5** & **\(\alpha\) = 0.9** \\ \hline CLUST1 & 0.6000 & 0.5778 & 0.6014 & 0.5838 & 246.6 & 226.51 & 298.62 & 229.91 \\ CLUST2 & 0.6000 & 0.5832 & 0.6021 & 0.5826 & 197.2 & 207.42 & 280.22 & 227.19 \\ CLUST3 & 0.6000 & - & - & 0.5817 & 152.6 & - & - & 173.02 \\ CLUST4 & 0.6000 & - & 0.6003 & 0.5819 & 53.9 & - & 101.89 & 52.07 \\ \cline{2-9} CLUST1 & \multicolumn{6}{c}{**rFC (g)**} & \multicolumn{6}{c}{**\(\Delta\)FC (\(\%\))**} \\ \cline{2-9} CLUST1 & 246.6 & 258.65 & 298.62 & 253.21 & - & 4.89 & 21.09 & 2.68 \\ CLUST2 & 197.2 & 231.65 & 280.22 & 252.28 & - & 17.47 & 42.10 & 27.93 \\ CLUST3 & 152.6 & - & - & 199.33 & - & - & - & 30.62 \\ CLUST4 & 53.9 & - & 101.89 & 78.21 & - & - & 89.04 & 45.10 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Results produced by a sensitivity to \(\alpha\) considering \(\alpha=0.1\), \(\alpha=0.5\) and \(\alpha=0.9\). \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**DM**} & \multicolumn{6}{c}{_SoC\({}_{f}\) (\(\star\))_} & \multicolumn{6}{c}{**FC (g)**} \\ \cline{2-9}  & **DP** & **_L1_** & **_L2_** & **_L3_** & **_DP_** & **_L1_** & **_L2_** & **_L3_** \\ \hline CLUST1 & 0.6000 & 0.5838 & 0.6020 & 0.6017 & 246.6 & 229.91 & 309.01 & 269.35 \\ CLUST2 & 0.6000 & 0.5826 & 0.6020 & 0.6022 & 197.2 & 227.19 & 299.63 & 255.55 \\ CLUST3 & 0.6000 & 0.5817 & - & - & 152.6 & 173.02 & - & - \\ CLUST4 & 0.6000 & 0.5819 & 0.6010 & 0.6010 & 53.9 & 52.07 & 88.09 & 90.33 \\ \cline{2-9} CLUST1 & \multicolumn{6}{c}{**rFC (g)**} & \multicolumn{6}{c}{**\(\Delta\)FC (\(\%\))**} \\ \cline{2-9} CLUST1 & 246.6 & 253.21 & 309.01 & 269.35 & - & 2.68 & 25.31 & 9.23 \\ CLUST2 & 197.2 & 252.28 & 299.63 & 255.55 & - & 27.93 & 51.94 & 29.59 \\ CLUST3 & 152.6 & 199.33 & - & - & - & 30.62 & - & - \\ CLUST4 & 53.9 & 78.21 & 88.09 & 90.33 & - & 45.10 & 63.43 & 67.59 \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Effects of a variation of the exploration strategy considering L1, L2 and L3. Since L1 is characterized by a very short exploration boost with respect to L2 (and even more with respect to L3), an additional analysis has been performed by assessing for the learning process of the agent during the very first episodes of the experiment.