Norm Deviation in Multiagent Systems: A Foundation for Responsible Autonomy
Authors: Amika M. Singh, Munindar P. Singh
IJCAI 2023 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We propose a conceptual foundation for norm deviation. ... Our analysis thus goes beyond previous studies of norm deviation and yields reasoning guidelines uniting norms and values by which to develop responsible agents. ... This study provides a conceptual foundation for responsible autonomy [Singh, 2022] based on the Habermasian validity claims and grounded in legal thinking and case law. ... Most of the above approaches are evaluated via examples crafted by the authors. But empirical validation is crucial since, to understand the suitability of agent behaviors or the analyses produced by formal tools, we must understand what people would do. ... In contrast, we adopt case law as a source of empirical knowledge about how laws are interpreted and applied. |
| Researcher Affiliation | Academia | Amika M. Singh1 and Munindar P. Singh2 1Harvard Law School 2North Carolina State University asingh@jd23.law.harvard.edu, mpsingh@ncsu.edu |
| Pseudocode | No | The paper provides an "argument scheme" as a logical structure but does not include any structured pseudocode or algorithm blocks typically found in computational papers. |
| Open Source Code | No | The paper does not contain any statements about releasing open-source code for the described methodology, nor does it provide any links to a code repository. |
| Open Datasets | No | The paper uses "case law as a source of empirical knowledge" for grounding its conceptual framework, but it does not utilize a dataset in the typical sense of machine learning experiments (e.g., for training models), nor does it provide access information for such a dataset. |
| Dataset Splits | No | The paper develops a conceptual framework and does not involve training models on datasets with specific data splits for validation or testing. |
| Hardware Specification | No | The paper is conceptual and theoretical, and does not report on computational experiments that would require a description of hardware specifications. |
| Software Dependencies | No | The paper is theoretical and does not describe any computational implementation or experiments that would necessitate listing specific software dependencies with version numbers. |
| Experiment Setup | No | The paper is theoretical and conceptual, and does not include details about an experimental setup, hyperparameters, or training configurations. |