TY - GEN
T1 - A Petri Net Formalism to Study Systems at Different Scales Exploiting Agent-Based and Stochastic Simulations
AU - Beccuti, M.
AU - Castagno, P.
AU - Franceschinis, G.
AU - Pennisi, M.
AU - Pernice, S.
N1 - Publisher Copyright:
© 2021, Springer Nature Switzerland AG.
PY - 2021
Y1 - 2021
N2 - The recent technological advances in computer science have enabled the definition of new modeling paradigms that differ from the classical ones in describing the system in terms of its components or entities. Among them, Agent-Based Models (ABMs) are gaining more and more popularity thanks to their ability to capture emergent phenomena resulting from the interactions of individual entities. However, ABMs lack a formal definition and precisely defined semantics. To overcome this issue we propose a new method exploiting Petri Nets as a graphical meta-formalism for modeling a system from which an ABM model with clear and well-defined semantics can be automatically derived and simulated. We aim to define a framework, based on a PN formalism, in which a system can be efficiently studied through both Agent-Based Simulation and classical Stochastic one depending on the study goal.
AB - The recent technological advances in computer science have enabled the definition of new modeling paradigms that differ from the classical ones in describing the system in terms of its components or entities. Among them, Agent-Based Models (ABMs) are gaining more and more popularity thanks to their ability to capture emergent phenomena resulting from the interactions of individual entities. However, ABMs lack a formal definition and precisely defined semantics. To overcome this issue we propose a new method exploiting Petri Nets as a graphical meta-formalism for modeling a system from which an ABM model with clear and well-defined semantics can be automatically derived and simulated. We aim to define a framework, based on a PN formalism, in which a system can be efficiently studied through both Agent-Based Simulation and classical Stochastic one depending on the study goal.
KW - Agent based modeling and simulation
KW - Extended stochastic symmetric Petri nets
KW - Stochastic simulation
UR - http://www.scopus.com/inward/record.url?scp=85121923950&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-91825-5_2
DO - 10.1007/978-3-030-91825-5_2
M3 - Conference contribution
AN - SCOPUS:85121923950
SN - 9783030918248
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 22
EP - 43
BT - Performance Engineering and Stochastic Modeling - 17th European Workshop, EPEW 2021, and 26th International Conference, ASMTA 2021, Proceedings
A2 - Ballarini, Paolo
A2 - Castel, Hind
A2 - Dimitriou, Ioannis
A2 - Iacono, Mauro
A2 - Phung-Duc, Tuan
A2 - Walraevens, Joris
PB - Springer Science and Business Media Deutschland GmbH
T2 - 17th European Performance Engineering Workshop, EPEW 2021, and the 26th International Conference on Analytical and Stochastic Modelling Techniques and Applications, ASMTA 2021
Y2 - 13 December 2021 through 14 December 2021
ER -