Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
7-2012
Abstract
Accurate analysis of the stochastic dynamics of multi-agent system is important but challenging. Probabilistic model checking, a formal technique for analysing a system which exhibits stochastic behaviors, can be a natural solution to analyse multi-agent systems. In this paper, we investigate this problem in the context of dispersion games focusing on two strategies: basic simple strategy (BSS) and extended simple strategies (ESS). We model the system using discrete-time Markov chain (DTMC) and reduce the state space of the models by applying counter abstraction technique. Two important properties of the system are considered: convergence and convergence rate. We show that these kinds of properties can be automatically analysed and verified using probabilistic model checking techniques. Better understanding of the dynamics of the strategies can be obtained compared with empirical evaluations in previous work. Through the analysis, we are able to demonstrate that probabilistic model checking technique is applicable, and indeed useful for automatic analysis and verification of multi-agent dynamics.
Keywords
Model Check, Multiagent System, Model Check Technique, Vickrey Auction, Statistical Model Check
Discipline
Programming Languages and Compilers | Software Engineering
Research Areas
Software and Cyber-Physical Systems
Publication
Proceedings of the 15th International Conference, Kuching, Sarawak, Malaysia, September 3-7
First Page
16
Last Page
30
ISBN
9783642327285
Identifier
10.1007/978-3-642-32729-2_2
Publisher
Springer Link
City or Country
Sarawak, Malaysia
Citation
HAO, Jianye; SONG, Songzheng; LIU, Yang; SUN, Jun; GUI, Lin; DONG, Jin Song; and LEUNG, Ho-fung.
Probabilistic model checking multi-agent behaviors in dispersion games using counter abstraction. (2012). Proceedings of the 15th International Conference, Kuching, Sarawak, Malaysia, September 3-7. 16-30.
Available at: https://ink.library.smu.edu.sg/sis_research/5025
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1007/978-3-642-32729-2_2