Building Strong Semi-Autonomous Systems
Authors: Shlomo Zilberstein
AAAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We examine the broad rationale for semi-autonomy and define 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 shlomo@cs.umass.edu |
| 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. |