## Line Graph: % Negative Objects vs. Epochs ### Overview The image depicts a line graph comparing the performance of five different configurations over 250 epochs. The y-axis represents "% Negative Objects" (ranging from 0% to 0.8%), and the x-axis represents "Epochs" (0 to 250). Five distinct data series are plotted, each with unique colors and markers, showing varying trends in negative object percentages over time. ### Components/Axes - **X-axis (Epochs)**: Labeled "Epochs," with ticks at 0, 50, 100, 150, 200, and 250. - **Y-axis (% Negative Objects)**: Labeled "% Negative Objects," with ticks at 0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, and 0.7. - **Legend**: Located in the bottom-right corner, with the following entries: - **SymDQN(AF)**: Green line with circular markers. - **SymDQN(AR)**: Purple line with triangular markers. - **SymDQN()**: Blue line with square markers. - **SymDQN(AR, AF)**: Orange line with diamond markers. - **Baseline**: Black line with triangular markers. ### Detailed Analysis 1. **SymDQN(AF) (Green)**: - Starts at ~0.35% at epoch 0. - Peaks at ~0.7% by epoch 250, maintaining the highest values throughout. - Shows moderate fluctuations but remains consistently above other series. 2. **SymDQN(AR) (Purple)**: - Begins at ~0.1% at epoch 0. - Rises steadily to ~0.55% by epoch 250. - Exhibits sharper fluctuations compared to SymDQN(AF). 3. **SymDQN() (Blue)**: - Starts at ~0.05% at epoch 0. - Increases to ~0.65% by epoch 250. - Shows significant variability, with peaks and troughs. 4. **SymDQN(AR, AF) (Orange)**: - Begins at ~0.15% at epoch 0. - Reaches ~0.6% by epoch 250. - Follows a relatively smooth upward trend with minor oscillations. 5. **Baseline (Black)**: - Starts at ~0.1% at epoch 0. - Ends at ~0.65% by epoch 250. - Displays erratic fluctuations, with values often overlapping other series. ### Key Observations - **SymDQN(AF)** consistently outperforms all other configurations, maintaining the highest % Negative Objects. - **SymDQN(AR, AF)** shows the second-highest performance, with a steady increase. - The **Baseline** exhibits the most variability, suggesting less stability compared to other configurations. - **SymDQN(AR)** and **SymDQN()** demonstrate similar trends but with distinct fluctuation patterns. ### Interpretation The data suggests that the **SymDQN(AF)** configuration is the most effective at maintaining higher % Negative Objects over time, potentially indicating superior performance in the evaluated task. The **Baseline**'s erratic behavior implies that the tested configurations generally outperform the default or control scenario. The **SymDQN(AR, AF)** configuration bridges the gap between the top-performing SymDQN(AF) and the others, highlighting the impact of combining AR and AF adjustments. The variability in SymDQN() and SymDQN(AR) suggests that additional tuning or context-specific factors may influence their effectiveness.