| tags: | |
| - PandaReachDense | |
| - PandaReachDense-v3 | |
| - panda-gym | |
| - deep-rl-course | |
| - a2c | |
| - reinforcement-learning | |
| - stable-baselines3 | |
| library_name: stable-baselines3 | |
| pipeline_tag: reinforcement-learning | |
| model-index: | |
| - name: a2c-PandaReachDense | |
| results: | |
| - task: | |
| name: reinforcement-learning | |
| type: reinforcement-learning | |
| dataset: | |
| name: PandaReachDense | |
| type: PandaReachDense | |
| metrics: | |
| - name: mean_reward | |
| type: mean_reward | |
| value: -0.45 +/- 0.12 | |
| # A2C Agent playing PandaReachDense | |
| This is a trained model of an A2C agent playing PandaReachDense using stable-baselines3 and panda-gym. | |
| - **Mean Reward**: -0.45 +/- 0.12 | |
| - **Result (mean - std)**: -0.57 | |