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..
Building Strong Semi-Autonomous Systems
Authors: Shlomo Zilberstein
AAAI 2015 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We examine the broad rationale for semi-autonomy and deο¬ne basic properties of such systems. Accounting for the human in the loop presents a considerable challenge for current planning techniques. We examine various design choices in the development of semi-autonomous systems and their implications on planning and execution. Finally, we discuss fruitful research directions for advancing the science of semi-autonomy. |
| Researcher Affiliation | Academia | Shlomo Zilberstein School of Computer Science University of Massachusetts Amherst EMAIL |
| Pseudocode | No | No pseudocode or algorithm blocks are present in the paper. |
| Open Source Code | No | The paper does not provide any statement about releasing source code or a link to a code repository. |
| Open Datasets | No | The paper does not describe any experiments or datasets used for training. |
| Dataset Splits | No | The paper does not describe any experiments or dataset splits for training, validation, or testing. |
| Hardware Specification | No | The paper does not describe any experiments, and therefore no hardware specifications are mentioned. |
| Software Dependencies | No | The paper does not describe any experiments that would require specific software dependencies with version numbers. |
| Experiment Setup | No | The paper does not describe any experiments, and thus no experimental setup details such as hyperparameters are provided. |