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 Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
Online Decision-Making for Scalable Autonomous Systems
Authors: Kyle Hollins Wray, Stefan J. Witwicki, Shlomo Zilberstein
IJCAI 2017 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We evaluate the approach in six scenarios within a realistic vehicle simulator and present its use on an AV prototype. |
| Researcher Affiliation | Collaboration | 1 College of Information and Computer Sciences, University of Massachusetts, Amherst, MA 01002 2 Nissan Research Center Silicon Valley, Sunnyvale, CA 94089 |
| Pseudocode | No | The paper does not contain any structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not include any explicit statements or links indicating that the source code for the described methodology is publicly available. |
| Open Datasets | No | The paper evaluates the approach 'in six scenarios within a realistic vehicle simulator developed by Realtime Technologies, Inc.' It describes the scenarios in Table 1, but does not provide access information (links, DOIs, citations with authors/year for a public dataset) for any publicly available or open dataset. |
| Dataset Splits | No | The paper describes evaluation in specific scenarios but does not provide explicit training, validation, or test dataset split percentages, sample counts, or references to predefined splits. |
| Hardware Specification | No | The paper mentions 'modest hardware' and 'fully-operational AV prototype' but does not provide specific details on CPU models, GPU models, memory, or other hardware components used for experiments. |
| Software Dependencies | No | The paper mentions using a 'realistic vehicle simulator developed by Realtime Technologies, Inc.' and the solver 'nova [Wray and Zilberstein, 2015]' but does not provide specific version numbers for these software components. |
| Experiment Setup | No | The paper describes the scenarios and baselines for evaluation but does not provide specific hyperparameter values, training configurations, or detailed system-level settings for the models or experiments. |