Assistive Teaching of Motor Control Tasks to Humans
Authors: Megha Srivastava, Erdem Biyik, Suvir Mirchandani, Noah Goodman, Dorsa Sadigh
NeurIPS 2022 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Through an extensive mix of synthetic and user studies on two motor control tasks parking a car with a joystick and writing characters from the Balinese alphabet we show that assisted teaching with skills improves student performance by around 40% compared to practicing full trajectories without skills, and practicing with individualized drills can result in up to 25% further improvement. |
| Researcher Affiliation | Academia | Megha Srivastava Stanford University megha@cs.stanford.edu Erdem Bıyık UC Berkeley ebiyik@berkeley.edu Suvir Mirchandani Stanford University suvir@cs.stanford.edu Noah D. Goodman Stanford University ngoodman@stanford.edu Dorsa Sadigh Stanford University dorsa@cs.stanford.edu |
| Pseudocode | Yes | Algorithm 1 Diverse Scenario Selection Input: Skill labels M e ξ for each ξ Ξe Input: Number of scenarios to be selected N s ... Algorithm 2 Individual Expertise Identification ... Algorithm 3 Individualized Drill Creation |
| Open Source Code | Yes | Our source code is available at https://github.com/Stanford-ILIAD/teaching. |
| Open Datasets | Yes | WRITING: We introduce a novel task of writing Balinese character sequences from the Omniglot dataset [41] ... PARKING: We use the Parking environment from Highway Env [42] |
| Dataset Splits | Yes | Students in both environments follow a sequence of pre-test scenarios, practice sessions (including skills or drill-based practice), and evaluation scenarios. ... We measure and report Reward Improvement, or the difference in average reward across 5 random evaluation scenarios and 2 random pre-test scenarios. |
| Hardware Specification | No | The main paper does not specify any particular hardware details such as GPU models, CPU models, or specific cluster configurations used for running experiments. While the checklist indicates this information is in the Appendix, it is not present in the main body of the paper. |
| Software Dependencies | No | The paper mentions 'Stable Baselines [43] implementation of Soft Actor-Critic' but does not provide specific version numbers for this or any other software dependencies. The full software details are likely deferred to the Appendix, but not included in the main text. |
| Experiment Setup | Yes | Drill Creation. We create one drill for each latent skill identified by SKILLEXTRACTOR for both PARKING (n = 3, Nrep = 1, Ntarget = 7, Ndrills = 1) and WRITING (n = 2, Nrep = 3, Ntarget = 8, Ndrills = 1) tasks. |