Int. J. of Simulation and Process Modelling   »   2018 Vol.13, No.1

 

 

Title: Modelling and analysis of multi-agent systems using UPPAAL SMC

 

Authors: Christian Nigro; Libero Nigro; Paolo F. Sciammarella

 

Addresses:
Laboratorio di Ingegneria del Software, Università della Calabria, DIMES, 87036 Rende (CS), Italy
Laboratorio di Ingegneria del Software, Università della Calabria, DIMES, 87036 Rende (CS), Italy
Laboratorio di Ingegneria del Software, Università della Calabria, DIMES, 87036 Rende (CS), Italy

 

Abstract: This paper proposes a novel approach to modelling and analysis of complex multi-agent systems. The approach is based on actors and asynchronous message passing, and exploits the UPPAAL statistical model checker (SMC) for the experiments. UPPAAL SMC is interesting because it automates simulations by predicting the number of executions capable of ensuring a required output accuracy, it uses statistical techniques (Monte Carlo-like simulations and sequential hypothesis testing) for extracting quantitative measures from the simulation runs, and it offers a temporal logic query language to express property queries tailored to the application needs. The paper describes the approach, clarifies its structural translation on top of UPPAAL SMC, and demonstrates its practical usefulness through modelling and analysis of a large scale and adaptive version of the Iterated Prisoner's Dilemma (IPD) problem. The case study confirms known properties, namely the emergence of cooperation under context preservation, that is when the player interaction links are preserved during the game, but it also suggests some new quantitative measures about the temporal behaviour which were not previously pointed out.

 

Keywords: modelling and simulation; multi-agent systems; MAS; actors; statistical model checking; UPPAAL; Iterated Prisoner's Dilemma; IPD.

 

DOI: 10.1504/IJSPM.2018.090275

 

Int. J. of Simulation and Process Modelling, 2018 Vol.13, No.1, pp.73 - 87

 

Submission date: 22 May 2017
Date of acceptance: 04 Sep 2017
Available online: 28 Feb 2018

 

 

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