## Bar Chart: Reward Comparison Across Environments ### Overview The image presents a bar chart comparing the performance (reward) of four different algorithms (ERL, RLVR, Qwen, and Olmo) across three different environments: FROZENLAKE, HOTPOTQA, and SOKOBAN. The chart is divided into three sub-charts, one for each environment. Each sub-chart displays the reward achieved by each algorithm in that environment. ### Components/Axes * **Title:** The chart lacks an overall title, but each sub-chart is titled with the environment name: FROZENLAKE, HOTPOTQA, and SOKOBAN. * **Y-axis:** Labeled "Reward," with a scale from 0.00 to 0.80 in increments of 0.20. * **X-axis:** Implicitly represents the different algorithms, with each algorithm having a corresponding bar in each sub-chart. * **Legend:** Located at the top-left of the image. * ERL: Green bar * RLVR: Blue bar * Qwen: White bar with blue diagonal stripes * Olmo: White bar with green diagonal stripes ### Detailed Analysis **FROZENLAKE** * ERL (Green): Reward of 0.94 * RLVR (Blue): Reward of 0.86 * Qwen (White with blue stripes): Not present * Olmo (White with green stripes): Reward of 0.66 **HOTPOTQA** * ERL (Green): Reward of 0.56 * RLVR (Blue): Reward of 0.45 * Qwen (White with blue stripes): Reward of 0.47 * Olmo (White with green stripes): Reward of 0.50 **SOKOBAN** * ERL (Green): Reward of 0.87 * RLVR (Blue): Reward of 0.06 * Qwen (White with blue stripes): Not present * Olmo (White with green stripes): Reward of 0.20 ### Key Observations * ERL consistently achieves high rewards in all three environments. * RLVR performs well in FROZENLAKE but struggles in HOTPOTQA and SOKOBAN. * Qwen and Olmo are only present in the HOTPOTQA and SOKOBAN environments. ### Interpretation The chart suggests that the ERL algorithm is the most robust across the tested environments, consistently achieving high rewards. RLVR's performance is highly environment-dependent, indicating it may be specialized for certain types of tasks. Qwen and Olmo show moderate performance in HOTPOTQA, but Olmo shows a low performance in SOKOBAN. The absence of Qwen and Olmo in FROZENLAKE suggests they may not be applicable or effective in that environment. The data highlights the importance of algorithm selection based on the specific environment and task requirements.