Knowledge Centred Simulation In Emergency Management Training Systems Rego Granlund Dept. of Computer and Information Science Linköping University S-581 83 Linköping, Sweden http://www.ida.liu.se/~reggr E-mail: [email protected] www-version: 1.0 02-Nov-1995

Abstract This paper describes the research, starting points, problems, and goals, for an on going project in which we are study the design and construction of computer simulation in decision training systems. In particular we are interested in the development of simulation systems for training of staff in emergency decision making and crisis management. The main problem that we are study is how to integrate pedagogical goals into the simulation models in a decision training system for complex dynamic systems. Key words : simulation, micro-world, emergency management, situated learning, situational awareness, autonomous agents

1

Introduction

2

Emergency Management

The Problem, Decision Training. Emergency Management, Complex Dynamic Systems, Distributed Decision Making, Natural Decision Making.

3

Emergency Management Training Emergency Management Training, Simulation Problems, Training Organisation.

4

Research Goal

5

The Micro-World C3Fire

Research Goal, Research Method, Contributions. C3Fire, Requirements met by C3Fire.

1

Introduction

This project deals with design and construction of computer simulation in decision training systems. In particular, with the development of simulation systems for training of commanders and staff in emergency decision making and crisis management. The main problem that we are study is the problem of how to integrate pedagogical goals into the simulation models in a decision training system for complex dynamic systems. The work has been carried out in a research group which focuses on the development and use of knowledge-based systems in real-life applications. This knowledge view is a base for our investigation, and its means that the work focuses on the problem of handling qualitative knowledge in simulated training environments. The project aims at providing design method ideas in form of important properties of training simulation system and of typical modelling difficulties. The Problem A common design strategy for simulations in training systems, is today often based on a strategy where an object oriented definition of the world is made from a physical model of the world. This strategy can be good if we want to do a simple simulation of the world. But if we want to use the simulation in a training situation, we often want to let pedagogical goals and wanted training situations, influence the simulation. This means that when we define the models and the implementation of the system we must know how the pedagogical goals influence the objects and the events that exist in the simulation. What we do not want to get is a modelling technique that focuses on quantitative data about the physical aspects of the world. We want to have a modelling technique that focuses on the qualitative knowledge about the concepts, the relation between the concepts in the training situation, and on the pedagogical goals of the training. I will refer to this type of simulation as knowledge centred simulation. With knowledge centred simulation we mean that the simulation should change its behaviour depending on the training goals and the knowledge of the students. This is a new and important philosophy when we want to create a simulation system. Decision Training Social systems, like emergency management systems (as forest fire fighting) and military systems, can be characterised by their dynamic behaviour created by co-operating actors. To achieve good performance in these systems, it is important that the people who command and control the system have good understanding of the system and their role in the system. This means that the commanders and staff need to be trained in real-world situations, so they can experience the dynamic behaviour of the system. In these kinds of systems it is often too expensive or humanly impossible to practise in real life situations. In these cases we need training systems where we can train commanders and staff in commanding and controlling a complex system. The goal of a training system for commanders and staff is that they in some way should experience the work situation that they will meet in a real situation. Typical things that they would experience in these kind of training systems are; • How the organisation and the world behave in different kind of common and critical situations. • How the distributed decision making influence their work. • How their work will change with different work-load situation. Important questions and problems for a training system as this is to define pedagogical training goals, and how to generate the world simulation that is needed for these pedagogical training goals.

2

Emergency Management

Emergency management system (as forest fire-fighting etc.), and military systems, can be defined as social systems, in which the decision makers goals are to define and organise a set of co-ordinate actions to reach a goal state and limit the negative consequences on the human, material and economic environment as far as possible. An abstract view of the world can in its simplest form be, a target system, (e.g. fire), and a hierarchical organisation, based on the staff (commanders) and its subordinates, (e.g. fire extinguish units), see Fig 1.

Commanders and staff

Fire extinguish units

Targetsystem Forest fire

Fig. 1: A complex dynamic system, containing; the staff, the emergency organisation, and the target system. The Target System: The target system is the system that is target of the emergency organisation's activity. Examples on target systems can be, the fire in forest fire extinguish operations, or the enemy forces in military operations. Civilian people can also be classified as a part of the target system. The target system can be classified as a complex dynamic system, which changes both autonomously and as a consequence of actions made on the system. The Staff: The commander's task in a staff is to command and control the emergency organisation. This means that they should collect information from the subordinates so that they get a situation awareness. Based on that they should plan and transmit orders to their subordinates, in order to direct and co-ordinate actions between the subordinate units. The staff is decision makers only and do not operate directly on the target system. (Artman 95) describe some of the staff’s work as, gather and sort out relevant and consistent information, make hypothesis about the system, plan one or several appropriate strategies, distribute work and resources to the subordinate units and co-ordinate actions between different units. The Emergency Organisation: In an emergency organisation, the staff’s subordinates are the staff’s tool in their task of controlling the target system. Examples of a subordinate unit can be, a fire fighting unit, an ambulance unit, or a military unit. In large hierarchical organisations as a military brigade, the organisation consist of several levels, companies, platoons, etc. The whole emergency organisation is only semi-controlled by the staff, and can as the target system be viewed as a complex dynamic system. Complex Dynamic System The complexity, and the dynamic and autonomous behaviour of the target-system and the emergency organisation, makes them hard to predict and control. The characteristics of these systems are that the control has to occur in real-time and it is difficult to provide a complete current state of the system because the dynamics of and the relations within the system are not visible. The difficulties in understanding the current state of the system, situation awareness, is an important problem and an important task to train. (Brehmer 94) has defined a complex dynamic system by the following criteria:

1. Complexity • It exists a set of disjunctive goals in the system. • It exists a set of related processes in the system. 2. Dynamics • The states of the system are changed both autonomously and as a function of the actions that the decision maker makes. • The decision makers have a limited time to make their decisions. 3. Opaqueness (not transparency) • Difficult to see the current state of the system. • Difficult to see what relations that exists in the system. Distributed Decision Making The decision making in an emergency organisation and in military systems has by (Brehmer 95) been classified as distributed decision making or team decision making. This means that the decision making or the cognition is distributed among the actors in the organisation. The system is also often based on a hierarchical organisation, where the decision makers work in different time scales. The people in the staff work in a higher time level that the subordinate decision makers, and are responsible for the strategic decisions. The problem of distributed decision making makes it important to train communication, and understanding of shared frameworks and goals. Team decision making is distributed decision making where the co-operating actors have different roles, tasks, and items of information in the decision process (Kline & Thordsen 1989; Orasanu & Salas 1993). Natural Decision Making The decision made by the staff can be classified as natural decision making. The decision making is not a task. The staff does not set out to ‘make a decision’, they set out to control their resources in a good way. Obtaining this goal requires making many decisions, but decision making is part of a larger activity, not an end in itself. Basic steps in naturalistic decision making are situation assessment and selection of a course of actions. According to (Lipshitz xx), the decision maker does a situation assessment where he or she size up the situation to a situation picture, based on that he or she makes diagnoses, hypotheses and decides a course of action. We can say that the decision maker reacts on the input information and processes it in a context of his or her own expertise. He or she is often not aware of any complex analytic thinking. One interesting decision model is the Recognition-Primed Decisions (RPD) model by (Klein 93). The RPD model is generated from several years of studying command and control performance, and it asserts that people use situation assessment to generate a plausible course of action and use mental simulation to evaluate that course of action.

3

Emergency Management Training

The thing that is hard to understand or get a good feeling for, by reading a book, is the dynamic behaviour that exists in a complex dynamic system. The dynamic behaviour can be viewed as a behaviour pattern of the target system or the emergency organisation, and should be learned by experience how it is to work as commander for the system. In these cases we can use emergency management training systems to bridge the gap between the theoretical studies and the work situations in the real world. Common training goals for the staff in an emergency management training are; Their task: Understand the work procedures, understanding the current situation, ‘situation awareness’, identifying future critical situations, etc. Distributed Decision: Experience how to exchange information with other persons in the organisation, the others persons needs and goals, and the importance of shared frameworks and goals. Dynamic Behaviour: Experience the dynamic behaviour of the organisation and the target system. Work Situation: Experience time pressure, high information load, inconsistent / missing information. There exist two important problems with this type of training, simulation of the surrounding world, and pedagogical control of the training sessions.

Simulation problems The simulation of the surrounding world should be is so realistic that it generates the same behaviour pattern ‘gestalts’ as the real world. The demands on the behaviour pattern gestalts are not so important for things that are not with in the training goals, but is very important for the behaviour that is connected to the training goals (Gestrelius 93). The main problem with the simulation is that the realworld systems often are based on co-operating actors. The basic problems are: Naturally Language Interaction: The interaction between the staff and the co-operating actors in the emergency organisation should be in natural language. A common way to solve this is to simplify and restrict the communication, or to use people that make a role-play of the actors in the environment. Activity Simulation: One important goal with the activity simulation is that the combination of all activities should generate the dynamic behaviour of the system. This means that it is hard to simplify a computer simulation and it is also hard for a role-playing person to simulate a number of activities. Training Session Control: The simulation should be controlled by the pedagogical goals. The simulation should change depending on the training goals, the students activity and knowledge. Training Organisation A common strategy to solve the simulation problem described above, is to use people that plays the roles of the humans in the simulated world. This means that we can use training assistants that does the communication with the staff and some mind-simulation of activities that the computer simulation does not manage to do. A training organisation can then be viewed as:

Staff

Training Manager

Training Assistants

Computer Simulation

Fig. 2: A common training organisation Staff: The trained staff should work in their normal environment. They should communicate with the training assistants, or in some situations with the training manager or the computer simulation. Training assistants: Their task is to make a realistic role-play of the humans that exist in the simulation. Their main task is to follow the pedagogical goals, communicate with the staff, react on the commands from the staff and on the information they get from the computer simulation. The main problem for the training assistant is to keep all the processes in the mind and not forget some important response from these activities. Besides the risk that the training assistant becomes overloaded, it is important that the training assistance have good experience and understanding of the pedagogical goals. One large problem for the training assistants is to co-ordinate and synchronise theirs activity so that wanted training situations generates. Training manager: The training manager should follow the activity of staff and direct the session so that it generates a proper training for the staff. Computer Simulation: The computer simulation should be used to support the training assistants with simulation of physical things. In more advanced simulations the computer can have models of human activities so that it can simulate human controlled activities. The simulation should follow the pedagogical goals and react on the students knowledge. The teaching strategies in this type of system use to be base on, briefing and debriefing.

4

Research Goal

The problem in focus is to see how we can support the training assistants with a computer simulation tool that simulates some of the activity simulations that the training assistants are responsible for. The main task is to examine the properties of the simulation-tool they may need, and how pedagogical goals can be integrated in to these simulations. Research goal The problem domain described above is the ground for this work. Based on this problem domain we have a specific research question, that is: • How will the pedagogy in situated learning theories influence the design of computer simulation in decision training systems? The aim of the work is to provide some answers to the question, based on our own interpretation of a literature study in the area, on a study of existing systems and on first-hand experience collected from previous projects and on design, implementation and evaluation of C3Fire, a decision training system. The aim is to bridge the gap between educational theories, dynamic systems theories and computer simulations. The contributions should be more on the methodological rather than on the technical level. The implementation techniques will not be used for improving those techniques in them selves. The goal is to show how these techniques can be used to produce better systems, in the pedagogical point of view. The long time research goal in this research is to define case tools, that supports some methodology to design simulations in emergency management decision training systems. Research Method Results from a study of existing training systems (Granlund 94ab), indicated that it should be a hard task to create an experimental simulation system. In these training systems, the surrounding world were to complex and the training goals were too unspecified, to be a good research task. On the basis of this we have selected to do an experimental simulation system in a micro-world. A micro-world means that we select some important properties from the real system and create a small and wellcontrolled environment for our experimentation. The goal of the micro-world system is that we want to have an experimentation platform where we can change different control strategies and study the performance of these. The performance could in this environment be empirically studied by doing different training sessions, where we can compare the trained peoples performance. The environment gives an ability to: • Investigate and train people in commanding and controlling a dynamic system. • Create a knowledge centred training environment. • Create a control structure so that we can produce pedagogical training sessions. • Train people in solving problems in a dynamic environment. Contributions The main contributions are: • C3Fire, an environment for investigation and training experimentation of distributed cognition and situational awareness. C3Fire is a, command, control and communication, experimental simulation environment. The system consists of a micro-world that can be used to demonstrate how a training system for forest fire extinguish commanders can be archived. • A discussion of the design, construction and evaluation of the C3Fire environment. The evaluation discussion is based on an experiment series, containing 15 * 4 hours experimentation, with 4 cooperating persons in the micro-world. The goal of the discussion is to give some guidelines that aim towards some methodologies for design and construct decision training systems. It might be worth pointing out that the intentions of the result presented in this work is not do give the truth, but to give some hints on guidelines that eventually will led to construction of better decision training systems.

5

The micro-world C3Fire

C3Fire is a, command, control and communication, experimental simulation environment with a forest fire domain. The system can be used for the generation of training sessions where a forest fire organisation can practise commanding and controlling fire-fighting units. In the C3Fire simulation it exists a forest fire, an environment with houses, different kinds of vegetation, and fire-fighting units that can be commanded and controlled by the people that run the system. The people that run the system are a part of a fire-fighting organisation and are divided into, the staff that are the trained people, and two fire-fighting unit chiefs that are the training assistants. The task of the staff is to have an overview picture of the situation and co-ordinate and schedule the fire-fighting units.

Trained people

Commanders and Staff

Role playning training assistances

Fire-fighting unit chiefs

Computer Simulation

Fire-fighting units and the fire

Fig. 3: C3Fire The requirements that are met by the C3Fire experimentation environment are: Dynamic Context: The decisions made by the staff are done in a dynamic context. Both the fire and the fire-fighting organisation are complex dynamic system, which changes both autonomously and as a consequence of actions made on the them. The fire-fighting units can in some degree be controlled by the decision makers in the staff. Distributed Decision: The task of extinguish the forest fire is distributed to a number of persons located as member of the staff and as fire-fighting unit chiefs. The decision making can be viewed as team decision making where the members have different roles, tasks, and items of information in their decision process. Time Scales: As in most hierarchical organisations the decision makers work in different time scales. The fire-fighting unit chiefs are responsible for the low level operation, as the fire-fighting, which is done in a short time scale. The staff work in a higher time level and are responsible for the coordination of the fire-fighting units and the strategic thinking. Training Experimentation: To be able to create pedagogical and knowledge adapted training situations, the environment and the behaviour of the computer simulation can be changed in a controllable manner. This is done by a scenario, that define the world and have a time controlled description of the world and the behaviour of the simulated actors. The system also makes a complete log over the session, with makes it possible to make a replay of the session. C3Fire is developed from D3Fire that is an experimental system for studies of distributed decision making in dynamic environments, created by (Svenmarck and Brehmer 92), Uppsala university, Sweden. More about C3Fire and the experimentation made with it can be read in the papers ‘C3Fire: A Training System For Commanders And Staff’ and ‘C 3Fire Training Experimentation One’.

References Artman, H. (1995). Team Decision Making and Distributed Cognition in Co-operative Work for Process Control. Linköping University, Sweden. Brehmer, B. (1991). Modern Information Technology: Time scales and Distributed Decision Making. and, Organisation for Decision Making in Complex Systems. in the book Distributed Decision Making: Cognitive Models for Co-operative Work. edited by Jens Rasmussen, Berndt Brehmer and Jacques Leplat, ISBN 0-471-92828-3, 1991. Brehmer, B. (1994). Verbal communication at seminary on, Distributed Decision Making, 4 Feb. 1994, in the course, Higher psychology, at Linköping University, Sweden. Brehmer, B. (1995). Distributed Decision Making In Dynamic Environments. Uppsala University, Sweden. Foa Report Nr. Gestrelius, K. (1993). Pedagogik i simuleringsspel - Erfarenhetsbaserad utbildning med överinlärningsmöjligheter. Pedagogisk Orientering och Debatt 100. Lund University, Sweden. Granlund. R. (1994a). InfSS Borensberg: A military training centre for commanders and staff. ASLAB-Memo 94-02, Linköping University, Sweden. Granlund. R. (1994b) Reflections on support tool for environment simulation in InfSS Borensberg. ASLAB-Memo 94-04, Linköping University, Sweden. Klein, G. A. (1993). A Recognition-Primed Decision (RPD) Model of Rapid Decision making. in the book, Decision Making in Action: Models and Methods. Edited by Gary A. Klein, Judith Orasanu, Roberta Calderwood, and Caroline E. Zsambok, 1993, ISBN 0-89391-794-X, pp 138 -- 147. Kline, G. A., Thordsen, M. (1989). Cognitive processes of the team mind. Ch2809-2/89/0000-0046. IEEE. Yellow Springs: Klein Associates Lipshitz, R. (1993). Converging Themes in the study of Decision Making in Realistic Settings. in the book, Decision Making in Action: Models and Methods. Edited by Gary A. Klein, Judith Orasanu, Roberta Calderwood, and Caroline E. Zsambok, 1993, ISBN 0-89391-794-X, pp 105 -- 109. Orasanu, J., Salas, E. (1993). Team Decision Making in Complex Environments. In G. Klein, J. Orasanu, R. Caldewood, C. E. Zambok (Eds.) Decision Making in Action: Models and Methods. New Jersey: Ablex Svenmarck, P., Brehmer, B. (1992) D3FIRE: An experimental paradigm for the studies of distributed decision making. in B. Brehmer (Ed.) (1992) Distributed decision making. Proceedings of the third MOHAWC workshop., 1991