On Computational Tractability for Rational Verification

Authors: Julian Gutierrez, Muhammad Najib, Giuseppe Perelli, Michael Wooldridge

IJCAI 2019 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical In this paper we show that the complexity of rational verification can be greatly reduced by restricting specifications to GR(1), a fragment of LTL that can represent most response properties of reactive systems. We also provide improved complexity results for rational verification when considering players goals given by mean-payoff utility functions arguably the most widely used quantitative objective for agents in concurrent and multiagent systems. In particular, we show that for a number of relevant settings, rational verification can be done in polynomial space or even in polynomial time.
Researcher Affiliation Academia Julian Gutierrez1 , Muhammad Najib1 , Giuseppe Perelli2 , Michael Wooldridge1 1Department of Computer Science, University of Oxford, UK 2Department of Informatics, University of Leicester, UK
Pseudocode Yes Algorithm 1: E-NASH of GR(1) games. and Algorithm 2: E-NASH of mp games.
Open Source Code No The paper does not provide any links to open-source code or state that the code for the described methodology is publicly available.
Open Datasets No This is a theoretical paper focusing on complexity results for formal verification problems. It does not involve empirical experiments with datasets, training, or public dataset availability.
Dataset Splits No This is a theoretical paper and does not involve empirical validation on datasets, thus no dataset split information for validation is provided.
Hardware Specification No The paper is theoretical and focuses on computational complexity. It does not describe any specific hardware used for experiments.
Software Dependencies No The paper describes theoretical algorithms and reductions. It does not mention any specific software dependencies with version numbers needed to replicate the work.
Experiment Setup No The paper is theoretical and focuses on complexity analysis and algorithm design. It does not describe an empirical experimental setup with hyperparameters or training configurations.