Romanian Journal of Information Science and Technology (ROMJIST)

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ROMJIST is a publication of Romanian Academy,
Section for Information Science and Technology

Editor – in – Chief:
Academician Dan Dascalu

Secretariate (office):
Adriana Neagu
Adress for correspondence: romjist@nano-link.net (after 1st of January, 2019)

Editing of the printed version: Mihaela Marian (Publishing House of the Romanian Academy, Bucharest)

Technical editor
of the on-line version:
Lucian Milea (University POLITEHNICA of Bucharest)

Sponsors:
• National Institute for R & D
in Microtechnologies
(IMT Bucharest), www.imt.ro
• Association for Generic
and Industrial Technologies (ASTEGI), www.astegi.ro

ROMJIST Volume 23, No. S, 2020, pp. S15-S27, Paper no. 651/2020
 

Monica Dascalu, Mihaela Malita, Adrian Barbilian, Eduard Franti and Gheorghe M. Stefan
Enhanced Cellular Automata with Autonomous Agents for Covid-19 Pandemic Modeling

ABSTRACT: The paper presents several experiments realized with an original model, the enhanced cellular automata with autonomous agents, in order to simulate the evolution of disease spreading. The simulations presented in the paper contain specific details of the actual Covid-19 infection: the atypicality of evolution of cases, the proximity required for infection, the long gestation time. The simulations show that the combination of cellular automata with autonomous agents can be used to model the evolution of a disease, due to its sensitivity to parameters associated to processes of infection and healing. The ability of the modeling system to find critical situations is also discussed. The details of the model include the topography of the space (contextual cellular automata), the timer associated with each autonomous agent to model the change of state (and the testing strategies), a FIFO memory that models the treatment facilities and the global control loop that introduces the central control of the system associated to the law enforcement and authorities. Abstract. The paper presents several experiments realized with an original model, the enhanced cellular automata with autonomous agents, in order to simulate the evolution of disease spreading. The simulations presented in the paper contain specific details of the actual Covid-19 infection: the atypicality of evolution of cases, the proximity required for infection, the long gestation time. The simulations show that the combination of cellular automata with autonomous agents can be used to model the evolution of a disease, due to its sensitivity to parameters associated to processes of infection and healing. The ability of the modeling system to find critical situations is also discussed. The details of the model include the topography of the space (contextual cellular automata), the timer associated with each autonomous agent to model the change of state (and the testing strategies), a FIFO memory that models the treatment facilities and the global control loop that introduces the central control of the system associated to the law enforcement and authorities.

KEYWORDS: Cellular Automata, Autonomous Agents, Covid-19, Pandemic Modeling

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