Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in [1].
Global Convergence of Online Optimization for Nonlinear Model Predictive Control
Authors: Sen Na
NeurIPS 2021 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We demonstrate the global convergence behavior of the proposed RTI scheme in a numerical experiment. |
| Researcher Affiliation | Academia | Department of Statistics University of Chicago Chicago, IL 60637 EMAIL |
| Pseudocode | Yes | Algorithm 1 An Adaptive RTI-based MPC Scheme |
| Open Source Code | Yes | The code is implemented in Julia 1.5.4 and is publicly available (with high resolution figures) at https://github.com/senna1128/Global-RTI-MPC. |
| Open Datasets | No | The paper does not use a traditional dataset, but rather simulates a '1D trigonometric perturbed LQR problem' with randomly generated initial iterates. There is no external, publicly available dataset mentioned with a link or citation. |
| Dataset Splits | No | The paper does not specify training, validation, or test dataset splits as it runs simulations with randomly generated initial iterates rather than using a fixed dataset. |
| Hardware Specification | No | The paper does not provide any specific hardware details used for running the experiments. |
| Software Dependencies | Yes | The code is implemented in Julia 1.5.4 and is publicly available (with high resolution figures) at https://github.com/senna1128/Global-RTI-MPC. |
| Experiment Setup | Yes | Table 1: Simulation Setups. ... For each case, we perform 1000 independent runs with randomly generalized initial iterate ( z0 0, ฮป 0 0), by letting (x0 k,0, u0 k,0, ฮป0 k,0) N(0, 25I), k. We stop the iteration if either t > N M (i.e. attains the iteration threshold) or Lt,0 ฯต = 10 8 (i.e. attains the error threshold). We let Bt = ยตI, t. |