Using C3Fire in reseach

Research Groups Resaerch groups that has or are using C3Fire in their research.
Research Studies Studies that has been performed with the C3Fire enviromnet.
Persons Persons involved in experiments or work with the C3Fire environment.
Publications Publications achived in research performed with the C3Fire environment.

Using C3Fire in reseach

The C3Fire environment

C3Fire is a micro-world (scaled-world) that provide an environment that allows controlled studies of collaborative decision making in a dynamic environment (Granlund et al 2001; Granlund 2002). In C3Fire players can perform team tasks as co-operation and coordination of actions and plans. The researchers can select some important characteristics of the real world and created a small and well-controlled simulation system that retains these characteristics. The system generates a task environment that have complex, dynamic and opaque characteristics, similar to the cognitive tasks that people normally encounter in real-life systems. The C3Fire micro-world are based on and developed from the ideas shown in the D3Fire micro-world (Svenmarck and Brehmer 1991; Svenmarck 1998).

The C3Fire system is highly configurative which make it possible for the researcher to configure the system to meet their research goal. The players' organisation and communication structures can be set up as wanted depending on the research goal. The user interfaces and communication tools can also be individual set-up for all players. When the collaboration is mediated via C3Fire's communication systems, the session design will impact on the collaborative process. This means that the researcher may have explicit control over some aspects of collaboration. The size of the organisation can be freely configuration from one to some thing around twenty players depending on the cognitive tasks and the speed of the used computer systems.

The domain, which is forest fire fighting, is of subsidiary interest and has been chosen because it creates a good dynamic environment for the players. It is possible to view the generated session as a simplified version of the work tasks and the division of labour conducted in an emergency task, a company business task, or a military task on a tactical level. The players are part of a fire-fighting organisation and can take on the roles of staff members or some unit chief in the fire-fighting organisation. The task of the staff is to gain an overview of the situation, and to co-ordinate and schedule the fire-fighting units so that they can extinguish the fire and save the important areas.

The generated task environment in micro-worlds of this type can be characterised by a dynamic context with distributed decision-making on different time scales (Brehmer & Dörner 1993). The decisions are taken in a dynamic context. The forest fire can be viewed as an ill-structured system that changes both autonomously and as a consequence of actions made on the system. This means that the forest fire is a complex dynamic autonomous system. The fire-fighting organisation can also be viewed as dynamic autonomous system, which in some degree can be controlled by the decision makers in the organisation. The decision-making is distributed over a number of persons and can be viewed as team decision-making where the members have different roles, tasks, and items of information available for their decision process. If the organisation is hierarchical, the decision makers can work on different time scales (Brehmer & Allard, 1991). The fire-fighting unit chiefs are responsible for the low-level operation, such as the fire-fighting, which is done in a short time frame. The staff works at a higher time level and are responsible for the co-ordination of the fire-fighting units and the strategic thinking. See figure for an example of a hierarchical organisation.

Figure 1. Example on a C3Fire environment setting.

The players in C3Fire are presented a number of different problems:

The players must engage in goal analysis; identifying priorities among goals, identifying sub-goals, resolving conflicting goals.
The players must learn environment, identify relations between the objects in the system. They must collect and integrate information and form hypotheses about the hidden structure of the environment.
The players must make prognoses concerning the future development in the system, and define action alternatives.
The players must make decisions, interact with the system and consider and evaluate their own strategies, over time.

Typical errors that players can make in the C3Fire environment are:

They do not understand regularities in the time-course, e.g., non-linear growth seen as linear, oscillations seen as chaotic.
They do not understand the side effects of their actions.
They tend to adopt an ad hoc behaviour.
They tend to adopt thematic vagabonding or encystment behaviour.
They have problems with delayed feedback.
They tend to overlook checking the outcome of the actions.


To be able to analyse the collaborative work in the C3Fire system, computer based monitoring are used (Granlund 2002). The monitoring is integrated in the simulation and all the information tools used by the players. During a session the C3Fire system creates a log with all events in the simulation and all computer mediated activities. The figure below, shows a view of the log process. The log process receives information from the simulation about the current activities in the simulated world. It also receives information about individual work, in terms of marks in the personal Map (GIS), and on the collaborative work in terms of information about the e-mail communication and the use of the distributed GIS and diary.

Figure 2. The log process in the C3Fire environment.

When the log information is centralised to the session server, it can be used in three main ways: quantitative analysis, situation detection and session replay. The session replay function and some quantitative analysis are integrated in the C3Fire environment while situation detection and advanced quantitative analysis are supported by the generated log information. The log information are stored in structured log files and in a SQL database which make it possible for the researchers to process the session information in an advanced manner.


Examples on four analysis goals that can be performed on the log information generated by the C3Fire system are: the effectiveness of the teams, the information distribution in the organisation, the students' situation awareness, and the students' work and collaboration methods (Granlund In Press).

Effectiveness of the Teams One way to evaluate the sessions and see if the team has performed well is to use some kind of scoring system. A scoring system should change depending on the goal and the task given to the players. A typical scoring system is to count the burned down area and destroyed objects.
Information Distribution One way to analyse the players is to observe how they collaborate. This can be done by analysing the communication between the players. Examples of analysing the communication and co-operation are to perform flow analysis and message classification of the email, GIS and diary based communication. When using message classes as commands, reports, questions, etc. it is possible get an indication of the collaboration process used by the players.
Situation Awareness To be able to perform a situation awareness analysis the C3Fire environment is equipped with a Map system (GIS, Geographic Information System) where the subjects could insert their view of the state during the session. Based on this feature, the manager can compare the actual state in the simulation with the information that the subjects had constructed in their GIS or communicated with the mail or diary tool. The GIS tool makes it possibility to measure the accuracy in terms of the type of information and the time difference between the time of the simulated activity and the time of the insertion in the GIS.
Work and Collaboration Methods If advanced message classification methods are used it can be possible to detect the players work and collaboration methods. An example is to classify the communication between the staff members and the chiefs in the fire-fighting organisation, and count the number of mission orders and commando orders. This may indicate the type of command.


The following references are used on this www page.

Brehmer, B. & Allard, R. (1991).
Modern Inormation Technology: Timescales and Distributed Decision.
In Distributed Decision Making: cognitive models for co-operative work,
J. Rasmussen, B. Brehmer & J. Leplat (eds.) pp. 319-334 John Wiley & Sons,
New York. ISBN 0-471-92828-3.

Brehmer, B. & Dörner, D. (1993).
Experiments With Computer-Simulated Microworlds:
Escaping Both the Narrow Straits of the Laboratory and the Deep Blue Sea of the Field Study.
In Computers in Human Behaviour, Vol. 9. pp.171-184 1993.

Granlund R, Johansson B, Persson M. (2001).
C3Fire a Micro-world for Collaboration Training in the ROLF environment.
In proceedings to SIMS 2001 the 42nd Conference on Simulation and Modelling,
Simulation in Theory and Practice. Organized by Scandinavian Simulation Society,
Porsgrunn, Norway, 8-9 October.

Granlund R. (2002).
Monitoring Distributed Teamwork Training
Ph.D. Thesis at Department of Computer and Information Science,
Linköping University, Sweden, 2002. ISBN 91-7373-312-1.

Granlund R. (In Press).
Monitoring experiences from command and control research with the C3Fire microworld
in Journal Cognition, Technology and Work.

Svenmarck, P., & Brehmer, B. (1991)
D3Fire, an experimental paradigm for the study of distributed decision making.
In B. Brehmer (ed.). Distributed Decision Making.
Proceedings of the Third MOHAWC Workshop, Belgirate, Italy, 15?17 may 1991.
Roskilde: Risö National Laboratory.

Svenmarck P. (1998)
Local Co-ordination in Dynamic Environments: Theories and Co-ordination support.
Liu-Tek-Lic-1998:52. ISBN 91-7219-281-X.