A Simple Probabilistic Extension of Modal Mu-calculus
Authors: Wanwei Liu, Lei Song, Ji Wang, Lijun Zhang
IJCAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this paper, we present a natural and succinct probabilistic extension of µcalculus, another prominent logic in the concurrency theory. We study the relationship with PCTL. Surprisingly, the expressiveness is highly orthogonal with PCTL. The proposed logic captures some useful properties which cannot be expressed in PCTL. We investigate the model checking and satisfiability problem, and show that the model checking problem is in UP co-UP, and the satisfiability checking can be decided via reducing into solving parity games. |
| Researcher Affiliation | Academia | Wanwei Liu School of Computer Science, National University of Defense Technology, Changsha, P. R. China Lei Song University of Technology, Sydney, Australia Ji Wang State Key Lab. of HPC, National University of Defense Technology, Changsha, P. R. China Lijun Zhang State Key Lab. of Computer Science, Institute of Software, CAS, Beijing, P. R. China |
| Pseudocode | No | No structured pseudocode or clearly labeled algorithm blocks were found in the paper. |
| Open Source Code | No | The paper focuses on theoretical contributions (logic, expressiveness, decidability) and does not describe an implementation. Therefore, no access to source code for the methodology is provided. |
| Open Datasets | No | The paper is theoretical and does not conduct experiments on datasets; therefore, no information regarding publicly available or open datasets for training is provided. |
| Dataset Splits | No | The paper is theoretical and does not involve empirical data or experiments; therefore, no specific dataset split information for validation is provided. |
| Hardware Specification | No | The paper is theoretical and does not describe any computational experiments; therefore, no specific hardware details used for running experiments are provided. |
| Software Dependencies | No | The paper is theoretical and does not describe any computational experiments or implementations; therefore, no specific software dependencies with version numbers are provided. |
| Experiment Setup | No | The paper is theoretical and does not describe any empirical experiments; therefore, no specific experimental setup details, hyperparameters, or training configurations are provided. |