**5. Conclusions**

22 Will-be-set-by-IN-TECH

**Political Definition** Being slightly similar to the previous conception, the political definition claims that the disaster definition comes from a political standpoint, even if the event could be accepted as a disaster for the other conceptions. On the other hand, by political demand, a situation that could not be portrayed as disaster may be addressed as such. Quarantelli stated that for those who define disasters by this definition "the formal designation can make a difference in everything from mitigation and prevention, to response and recovery activities."(Quarantelli, 1981). Therefore, a political decision on the matter of disasters can make all the difference between prevention, fast response / recovery and further damage

**Unbalance in the Demand-Capacity** This final conception takes a disaster as a type of crisis situation or a social occasion. An event is considered a disaster if the demands for urgent actions due to a threat to high priority values and the resources available do not meet such demands. Quarantelli recalls Erwin Goffman when he used the term occasion, which is related to "non-routine and emergent collective behavior". Thus, if the situation requires an unusual and new social behavior to balance the needs and the resources found in the

These concepts ranged from a purely physical approach to social related approaches and a social behavior approach. However, the concepts can be analyzed on a second point of view: the first concepts are more physical-specific centric, which means the physical component is relevant and in order to study the event a very specific look is required. A diverse physical

In turn, the final concepts are more social-generic centric, which lead to more generalized perception of disasters, an attempt to find common elements between disasters caused by

In a science committee which discussed the similarities between different types of disasters,

"The comparisons attempted clearly showed a conscious belief that trying to perceive phenomena which are not usually grouped together within the same framework, might prevent us from being partially blind in the way it was stated at the beginning of this paper"

In other words, when the researcher sees disasters in a generalized perspective it is possible to notice certain elements that could not be seen if the focus was just in a specific kind of disaster. Quarantelli's statement key word is **framework**. If a framework is designed for disasters in

Quarantelli endorsed a social-generic centric view for disasters, especially when "the problems are divided by time stage, by functions or levels of response"(Quarantelli, 1981). He mentioned Ralph Turner (from the Emergent Norm Theory) who stated "that much of what we know about how people respond to threats and warnings for other dangerous possibilities, is equally applicable to prediction scenarios for earthquakes". On the other hand, that does not imply that the specific study of earthquakes is unnecessary; seismologists still need to analyze earthquakes as much detailed as possible, treating earthquakes as disaster agents. For social and behavioral scientists, though, the best approach is accepting earthquake as

general, that means it could be applied to any sort of disaster with minimal effort.

control;

occasion, that situation leads to a disaster.

agent implies a diverse analysis.

different physical agents.

(Quarantelli, 1981).

Quarantelli pointed out that

members of a more generic class.

The panic in crowds' phenomenon has been studied for decades by many researchers. Such study is important for predicting and evaluating human behavior patterns in disasters. Although natural disasters are becoming more predictable, their outcomes cannot be easily foreseen. Panic in crowds works as a complex system, which implies that analyzing each individual and element alone does not provide the big picture required to understand the event as a whole. A broader view can notice the behavioral patterns that emerge from the interactions among individuals and it is more suitable for studying hazardous events, such as floods and earthquakes.

Simulating a disaster in real-life is dangerous and unethical. The usage of computer simulations allows the disaster event to happen in a controlled environment with no human

da Silva, V., Marietto, M. & Ribeiro, C. (2008). A multi-agent model for the micro-to-macro

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dos Santos França, R., das Graças B. Marietto, M. & Steinberger, M. B. (2009). A multi-agent

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Mackay, C. & Baruch, B. (1932). *Extraordinary popular delusions and the madness of crowds*, Barnes

Quarantelli, E. (1981). An agent specific or an all disaster spectrum approach to

Quarantelli, E. L. (1975). Panic behavior: Some empirical observations, *American Institute of*

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socio-behavioral aspects of earthquakes?

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loss of any kind. If modeled right, behavioral patterns can be extracted from the panic situation described by the simulation model. Such patterns might help disaster control groups to train people which it will minimize human and material losses. Also, it helps architects, technicians and engineers in designing buildings, rooms and other tools so they have a lower impact on the evacuation procedures during a crisis. Finally, simulations can be used to check and validate new ideas and to propose and check "what-if" scenarios that could be unfeasible to replicate in real-life.

Since panic in crowds is a complex system, a multi-agent based simulation is the best choice to model this kind of phenomenon. This chapter did a historical overview of the collective behavior's studies, since their early ages when collective behavior had a sense of wrongdoing and error up to common, still not institutionalized, social behaviors and the panic in crowds' theories. Everything was bound so further studies could be accomplished and a deeper discussion about the social elements of panic situations could happen.

After that, a simulation model based on the symbolic interactionism and the emergent norm approaches was presented. The model strictly followed the collective behavior formation steps analyzed by the aforementioned approaches and expanded it with computational tools such as expert systems and fuzzy logic. The conceptual model was tailored for fire incidents and a computation model was built, showing that the model can be applied and the fire incident simulation is possible.

Then, a key question was addressed: if it would be possible to use the same model for disasters such as earthquakes. The definition of disaster itself was put into question. As it said earlier, by looking the panic situations as complex systems, a broader view achieves better results than a physical agent focused analysis. Henceforth, the model presented by this chapter could be used for any kind of panic situation, including earthquakes, with minimal adjustments required.

Thanks to the theory and the simulation presented here, new lines of research could be derived. For instance, it would be possible to analyze composite panic situations, such as fire caused by an earthquake, as well as to identify the hazardous and complexity levels of such phenomena which are great pieces of information for authorities and damage control groups so they might create better procedures and allocate resources in critical situations.

#### **6. References**


URL: *http://jasss.soc.surrey.ac.uk/7/3/4.html*

24 Will-be-set-by-IN-TECH

loss of any kind. If modeled right, behavioral patterns can be extracted from the panic situation described by the simulation model. Such patterns might help disaster control groups to train people which it will minimize human and material losses. Also, it helps architects, technicians and engineers in designing buildings, rooms and other tools so they have a lower impact on the evacuation procedures during a crisis. Finally, simulations can be used to check and validate new ideas and to propose and check "what-if" scenarios that could be unfeasible

Since panic in crowds is a complex system, a multi-agent based simulation is the best choice to model this kind of phenomenon. This chapter did a historical overview of the collective behavior's studies, since their early ages when collective behavior had a sense of wrongdoing and error up to common, still not institutionalized, social behaviors and the panic in crowds' theories. Everything was bound so further studies could be accomplished and a deeper

After that, a simulation model based on the symbolic interactionism and the emergent norm approaches was presented. The model strictly followed the collective behavior formation steps analyzed by the aforementioned approaches and expanded it with computational tools such as expert systems and fuzzy logic. The conceptual model was tailored for fire incidents and a computation model was built, showing that the model can be applied and the fire

Then, a key question was addressed: if it would be possible to use the same model for disasters such as earthquakes. The definition of disaster itself was put into question. As it said earlier, by looking the panic situations as complex systems, a broader view achieves better results than a physical agent focused analysis. Henceforth, the model presented by this chapter could be used for any kind of panic situation, including earthquakes, with minimal adjustments

Thanks to the theory and the simulation presented here, new lines of research could be derived. For instance, it would be possible to analyze composite panic situations, such as fire caused by an earthquake, as well as to identify the hazardous and complexity levels of such phenomena which are great pieces of information for authorities and damage control groups so they might create better procedures and allocate resources in critical situations.

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