ASPiRe: Adaptive Skill Priors for Reinforcement Learning
Authors: Mengda Xu, Manuela Veloso, Shuran Song
NeurIPS 2022 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Our experiments demonstrate that ASPi Re can significantly accelerate the learning of new downstream tasks in the presence of multiple priors and show improvement on competitive baselines. We evaluate our method in three modified environments from D4RL [48] and one modified environment from robosuite environment [49]. |
| Researcher Affiliation | Collaboration | Mengda Xu 1, 2, Manuela Veloso 2,3, Shuran Song 1 1 Department of Computer Science, Columbia University 2 J.P. Morgan AI Research 3 School of Computer Science, Carnegie Mellon University (emeritus) |
| Pseudocode | Yes | Algorithm 1 ASPi Re Algorithm |
| Open Source Code | Yes | The code is in the supplement material. We provide the codes to regenerate the datasets and downstream task learning and all instructions are inside readme.md |
| Open Datasets | Yes | We evaluate our method in three modified environments from D4RL [48] and one modified environment from robosuite environment [49]. We use the D4RL benchmark and cite in the section 4. |
| Dataset Splits | Yes | Did you specify all the training details (e.g., data splits, hyperparameters, how they were chosen)? [Yes] See appendix A.4 |
| Hardware Specification | Yes | Did you include the total amount of compute and the type of resources used (e.g., type of GPUs, internal cluster, or cloud provider)? [Yes] See appendix A.4 |
| Software Dependencies | No | No specific software version numbers (e.g., Python 3.x, PyTorch 1.x) are explicitly mentioned in the paper's main text or checklist for reproducibility. |
| Experiment Setup | Yes | See appendix A.4 for details on environment, data collection process and training. Did you specify all the training details (e.g., data splits, hyperparameters, how they were chosen)? [Yes] See appendix A.4 |