Reasoning About Agents That May Know Other Agents’ Strategies

Authors: Francesco Belardinelli, Sophia Knight, Alessio Lomuscio, Bastien Maubert, Aniello Murano, Sasha Rubin

IJCAI 2021 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical We study the semantics of knowledge in strategic reasoning. ... We put forward a novel semantics for Strategy Logic with Knowledge that cleanly models whose strategies each agent knows. We study how adopting this semantics impacts agents knowledge and strategic ability, as well as the complexity of the model-checking problem. ... Theorem 1. Model checking SLK is undecidable, even when restricted to CGS with hierarchical information. ... Theorem 4. Model checking SLKinf on CGS with public actions is decidable.
Researcher Affiliation Academia Francesco Belardinelli1 , Sophia Knight2 , Alessio Lomuscio1 , Bastien Maubert3 , Aniello Murano3 and Sasha Rubin4 1Imperial College London, UK 2University of Minnesota Duluth, USA 3Universit a degli Studi di Napoli Federico II , Italy 4University of Sydney, Australia
Pseudocode No The paper defines syntax and semantics of SLKinf[BG] using formal grammar and logical statements but does not include any pseudocode or algorithm blocks.
Open Source Code No The paper does not contain any statements about releasing open-source code for the described methodology, nor does it provide links to any code repositories.
Open Datasets No This paper is theoretical and does not involve the use of datasets for training, evaluation, or any other purpose.
Dataset Splits No This paper is theoretical and does not involve the use of datasets, therefore no training/validation/test splits are discussed.
Hardware Specification No The paper describes theoretical formalizations and proofs; it does not include details about hardware specifications for any computational experiments.
Software Dependencies No The paper focuses on theoretical development and does not specify any software dependencies or their version numbers.
Experiment Setup No The paper is theoretical and does not include details about an experimental setup, hyperparameters, or training configurations.