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].

Two Forms of Responsibility in Strategic Games

Authors: Pavel Naumov, Jia Tao

IJCAI 2021 | Venue PDF | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical The paper shows that being blamable is de๏ฌnable through seeing to it, but not the other way around. In addition, it proposes a bimodal logical system that describes the interplay between the seeing to it modality and the individual knowledge modality.
Researcher Affiliation Academia 1King s College 2Lafayette College EMAIL, EMAIL
Pseudocode No The information is insufficient. The paper does not contain any figures, blocks, or sections labeled 'Pseudocode' or 'Algorithm', nor does it present structured steps formatted like code or an algorithm.
Open Source Code No The information is insufficient. The paper does not include any statements about releasing source code, nor does it provide a link to a code repository for the described methodology.
Open Datasets No The information is insufficient. The paper describes theoretical work and does not mention the use of any datasets for training or evaluation.
Dataset Splits No The information is insufficient. The paper describes theoretical work and does not refer to validation dataset splits.
Hardware Specification No The information is insufficient. The paper focuses on theoretical concepts and formal systems and does not mention any hardware specifications used for experiments.
Software Dependencies No The information is insufficient. The paper describes theoretical work and does not list any specific software components or their versions required to replicate the work.
Experiment Setup No The information is insufficient. The paper is theoretical and does not describe an empirical experimental setup, hyperparameters, or system-level training settings.