MANAGEMENT OF BIOLOGICAL AND CHEMICAL

MANAGEMENT OF BIOLOGICAL AND CHEMICAL INCIDENTS: SIMULATIONBASED DECISION SUPPORT
T. Otčenášková1, V. Bureš1, P. Čech1,2
1
Faculty of Informatics and Management, University of Hradec Králové, Hradec Králové,
Czech Republic
2
Faculty of Military Health Sciences, University of Defence & Armed Forces of the Czech
Republic, Hradec Králové, Czech Republic
ABSTRACT
Decision making processes during biological or chemical incidents represent a challenging
and demanding issue. This task constitutes of several complex activities and important
decisions. In case of unintentional accidents in agricultural plants or within related industries,
these decisions have to be made by personnel who are usually not primarily trained for such
situations. Therefore any available support tool, which can increase the probability of
successful management of these incidents, should be employed. The main aim is to minimize
the consequences, ensure the quality of products and protect people and animals and other
crucial assets. From the technological perspective, various approaches or principles have been
already applied and intended for computer-based support of biological or chemical incidents
management. Nevertheless, the multi-agent technologies can be also effectively utilized. As
an example, this paper presents model applicable for the management of biological or
chemical incidents created in the multi-agent NetLogo environment. The main contribution to
the scientific field includes the characterization of specifics related to the discussed type of
decision-making process. Moreover, within the paper the description of the simulation model
is provided, parameterization is explained, and areas for further research are outlined.
Key Words: Biological Incident Management; Chemical Incident Management; Decision
Making Process; Multi-agent Technologies; Simulation Modelling
INTRODUCTION
Currently, agriculture and related industries are closely connected with advances in the area of
biology and chemistry. Occasionally, biological or chemical incidents occur. These apparently
represent a considerable threat for our society and have more serious consequences than ever
before. This can be explained by more sophisticated biological agents and chemical
compounds, increasing value of endangered assets and also by fast development of
technologies within last few decades. The incidents can be categorized to these caused by the
biological or chemical weapons and the second group includes the unintentional occurrence of
such problems exemplified by the leakage of a dangerous substance from a plant or
laboratory, or natural incidence of a disease within animal herds. The intentional incidents are
usually easier manageable, because their focal point can be typically identified quickly and
localized more precisely. Therefore, the critical assets can be recognized faster and adequately
protected. The appropriate reaction to these incidents is conducted only by trained personnel,
usually pertaining to police, epidemiological or armed forces. On the other hand in case of
unintentional accidents, which occur within agricultural mills or plants, people responsible for
the management of such complex and difficult tasks are usually not trained enough for prompt
and professional decisions which would protect the critical assets. Therefore, the biological
and chemical incidents remain challenging as well as important task for both researchers and
practitioners. Considering the aforementioned reasons, a tool for decision support and for the
improvement of the decision effectiveness and consequences minimization needs to be used.
The main aim of this paper is to introduce the multi-agent based simulation, because it
provides with the advantages such as problem complexity elimination, incident scenario
modeling, or more effective resource planning and utilization. Moreover, the demands on
non-expert decision makers are decreased significantly. It ensures flexible and more precise
attitude to the incident management.
ACKNOWLEDGEMENT
This paper was written with the support of The Grant Agency of the Czech Republic (GACR),
Project No. 402/09/0662 „Decision Processes in Autonomous Systems“ and the Ministry of
Defence & Armed Forces of the Czech Republic, Project No. MO0FVZ0000604 „Information
Support of Crisis Management in Health Care”.
REFERENCES
AJELLI, M. - GONCALVES, B. - BALCAN, D. et al.: Comparing large-scale computational
approaches to epidemic modeling: Agent-based versus structured metapopulation models.
BMC Infectious Diseases, 10, 2010: 1:190.
AN, L.: Modeling human decisions in coupled human and natural systems: Review of agentbased models. Ecological Modelling, 229, 2011: 25-36.
AXELROD, R.: Advancing the Art of Simulation in the Social Sciences. In: RENNARD, J.P.: Handbook of Research on Nature Inspired Computing for Economy and Management.
Hershey-PA, USA: Idea Group, 2005.
BURES, V. et al.: Systems Thinking as a Basis for Ambient Intelligence. In: Proceedings of
11th Annual SIGCSE Conference on Innovation and Technology in Computer Science
Education, Bologna, Italy, 26-28 June 2006. New York, USA, ACM, 2006, p. 318.
COMMITTEE ON TOXICOLOGY, National Research Council: Review of Acute HumanToxicity Estimates for Selected Chemical Warfare Agents. Washington, D.C., USA: National
Academic Press, 1997.
CECH, P. - BURES, V.: Advanced Technologies in e-Tourism. In: Proceedings of the 9th
WSEAS International Conference on Applied Computer Science, Genova, Italy, 17-19
October 2009. Stevens Point, USA, WSEAS, 2009, pp. 85-92.
DION, E. - VANSCHALKWYK, L. - LAMBIN, E.F.: The landscape epidemiology of footand-mouth disease in South Africa: A spatially explicit multi-agent simulation. Ecological
Modelling, 222, 2011: 2059-2072.
GRIMM, V., et al.: A standard protocol for describing individual-based and agent-based
models. Ecological Modelling, 198, 1-2, 2006: 115-126.
HURD, H.S. - KANEENE, J.B.: The application of simulation models and systems analysis
in epidemiology: a review. Preventive Veterinary Medicine, 15, 1993: 81-99.
IORDAN, V. - NAAJI, A. - CICORTAS, A.: Deriving Ontology Using Multi-agent Systems.
WSEAS Transactions on Computers, 7, 6, 2008.
KAHN, B.E. et al.: Examining Medical Decision Making from a Marketing Perspective.
Marketing Letters, 8, 3, 1997: 361-375.
LINARD, C. et al.: A multi-agent simulation to assess the risk of malaria re-emergence in
southern France. Ecological Modelling, 220, 2009: 160-174.
NETLOGO, c1999-2010: NetLogo. NetLogo, 2011. Available at:
http://ccl.northwestern.edu/netlogo/. Accessed: 22 January 2011.
NOVOTNY, O. - POUR, J. - SLANSKY, D.: Business Intelligence. Prague, Czech Republic:
Grada Publishing, 2005.
OLSEVICOVA, K.: Refined concept map of agent-based systems. In: Proceedings of the
International Conference on Engineering Education and International Conference on
Education and Educational Technologies, Corfu, Greece, 2011. WSEAS, 2011, pp. 274-277.
OTCENASKOVA, T. - BURES, V. - CECH, P.: Conceptual modelling for management of
public health in case of emergency situations. In: Proceedings of the International Conference
on Knowledge Engineering and Ontology Development (KEOD 2011), Paris, France, October
2011. Lisbon, Portugal, SciTePress, 2011, pp. 344-348.
O'NEIL, C.A. - SATTENSPIEL, L.: Agent-Based Modeling of the Spread of the 1918-1919
Flu in Three Canadian Fur Trading Communities. American Journal of Human Biology, 22, 6,
2010: 757-767.
PANUS, J.: Parallel Computing for Modified Local Search. In: FUJITA, H. - Sasaki J. (eds.)
ACS'10 Proceedings of the 10th WSEAS International Conference on Applied Computer
Science, Iwate, Japan, 4-6 October 2010. Stevens Point, USA, ACM, 2010, pp. 508-513.
PAULK, M.C. et al.: The Capability Maturity Model: Guidelines for Improving the Software
Process. Reading, USA: Addison-Wesley, 1995.
STEPANKOVA, O. - MARIK, V. - LHOTSKA, L.: Distributed Artificial Intelligence
(translated from Distribuovana uměla inteligence). In: Artificial Intelligence 2 (translated
from Uměla inteligence 2). (In Czech) Prague, Czech Republic: Academia, 1997.
TSAI, M.T. - CHERN, T.C. - CHUANG, J.H. et al.: Efficient Simulation of the Spatial
Transmission Dynamics of Influenza. PLoS ONE, 5, 11, 2010.
URBANCOVA, H. - KONIGOVA, M.: New Management Disciplines in the Area of
Business Continuity. Scientia Agriculturae Bohemica, 1, 2011: 37-43.
USAMRIID: USAMRIID’s Medical Management of Biological Casualties Handbook. 6th
edition, Maryland, 2005. Available at:
http://www.usamriid.army.mil/education/bluebookpdf/USAMRIID%20BlueBook%206th%20
Edition%20-%20Sep%202006.pdf. Accessed: 7 January 2011.
VANICEK, J. - VOSTROVSKY, V.: Agriculture Knowledge Modelling by Means of Fuzzy
Decision Tables. Scientia Agriculturae Bohemica, 2-SPECIAL, 2008: 163-167.
MANAGEMENT BIOLOGICKÝCH A CHEMICKÝCH INCIDENTŮ: PODPORA
ROZHODOVÁNÍ ZALOŽENÁ NA SIMULACÍCH
ABSTRAKT
Rozhodovací procesy v průběhu biologických a chemických incidentů představují náročnou a
komplexní problematiku, protože zahrnují řadu důležitých rozhodnutí. V případě
neúmyslných nehod v zemědělství a příbuzných průmyslových odvětvích jsou tato rozhodnutí
zpravidla činěna lidmi, kteří nejsou primárně vyškoleni pro obdobné situace. Nejen z tohoto
důvodu je vhodné využít dostupných nástrojů, které by zvýšily pravděpodobnost úspěšnosti
managementu podobných havárií. Hlavním cílem je eliminace následků, zvýšení kvality
produktů a ochrana lidí, zvířat a dalších důležitých aktiv. Z technologického hlediska byla již
dříve využívána počítačová podpora managementu biologických a chemických incidentů.
Nicméně multiagentové technologie představují nástroj, jehož potenciál není v této oblasti
dostatečně rozvinut. Tento článek tak představuje model vytvořený v multiagentovém
prostředí NetLogo, který je použitelný pro podporu managementu biologických a chemických
incidentů. Hlavní přínos zahrnuje především charakteristiku specifik diskutovaných
rozhodovacích procesů. Dále je popsán daný simulační model, vysvětlena jeho parametrizace
a nastíněny jsou i oblasti dalšího výzkumu.
Klíčová slova: management biologické havárie; management chemické havárie;
multiagentové technologie; rozhodovací proces; simulační modelování
Contact
Ing. Tereza Otčenášková, BA; address: Faculty of Informatics and Management, University
of Hradec Králové, Rokitanského 62, 500 03 Hradec Králové, Czech Republic; telephone
number: +420 493 332 259; e-mail: [email protected]