2 THE METHOD
The method that we use for conceptual modelling
for realistic training scenarios is agent-oriented
modelling (Sterling and Taveter, 2009). We prefer
this method over other alternatives because it
straightforwardly enables to model a system of goals
to be achieved by a training scenario, as well as the
activities to be performed by players in the scenario
different participants and the criteria for evaluating
these activities should be clearly outlined. We also
have a lot of positive anecdotal experience of
applying AOM in the related domain, where AOM
was successfully applied for developing a training
resource to teach secondary school students to
respect people with Asperger’s Syndrome.
Agent-oriented modelling is an approach for
modelling and simulating the behaviours of complex
socio-technical systems where a problem domain is
first conceptualized in terms of the goals to be
achieved by the system, the roles required for
achieving them, and the domain entities embodying
the required knowledge. The roles are thereafter
mapped to the agents playing the roles, the goals – to
the activities performed by the agents, and the
domain entities – to the items of knowledge held by
the agents. As we are concerned with “human-in-
the-loop” simulations, the term “agent” subsumes
both human agents and man-made agents –
softwareagents simulating humans. Conceptually,
we consider models as abstractions reducing the
complexity of a system for better understanding of
the system’s particular aspects and their impact on
its behaviour.
The types of models proposed by agent-oriented
modelling (AOM) are represented in Table 1. In
addition to representing for each model the
abstraction layer (analysis, design, or simulation),
Table 1 maps each model to the vertical viewpoint
aspect of interaction, information, or behaviour.
Each cell in the table represents a specific viewpoint.
We will next give an overview of agent-oriented
models relevant for understanding this article
proceeding by viewpoints. These models are
distinguished by using a bold font in Table 1.
From the viewpoint of behaviour analysis, a goal
model can be considered as a container of three
components: goals, quality goals, and roles (Sterling
and Taveter, 2009). A goal is a representation of a
functional requirement for the simulation system,
describing the phenomenon or process to be
simulated. A quality goal, as its name implies, is a
non-functional or quality requirement of the system.
Goals and quality goals can be further decomposed
into smaller related subgoals and subquality goals.
The hierarchical structure is to show that the
subcomponent is an aspect of the top-level
component. Goal models also determine roles that
are capacities or positions that agents playing the
roles need to contribute to achieving the goals. The
notation for representing goals and roles is shown in
Table 2 (Sterling and Taveter, 2009).
From the viewpoint of interaction analysis, the
properties of roles are expressed by role models. A
role model describes the role in terms of the
responsibilities and constraints pertaining to the
agent(s) playing the role.
From the viewpoint of interaction design,
interaction models represent interaction patterns
between agents of the given types. They are based
on responsibilities defined for the corresponding
roles. In this paper, we represent interaction models
by means of action events and non-action events. An
action event is an event that is caused by the action
of an agent, like sending a message or starting a
machine. An action event can thus be viewed as a
coin with two sides: an action for the performing
agent and an event for the perceiving agent. A
message is a special type of action event—
communicative action event—that is caused by the
sending agent and perceived by the receiving agent.
On the other hand, there are non-action events that
are not caused by actions. Non-action events include
exogenous events. An exogenous event is a kind of
event whose creating agent we are not interested in.
Finally, from the viewpoint of behaviour design
,
behaviour models describe the behaviours of
individual agents (Sterling and Taveter, 2009).
Table 1: The Model Types of Agent-Oriented Modelling.
Viewpoint aspect
Abstraction
layer
Interaction Information Behaviour
Analysis
Role
models and
organization
model
Domain
model
Goal models
and
motivational
scenarios
Design
Agent
models and
interaction
models
Knowledge
models
Scenarios and
behaviour
models
Simulation Platform-specific models
3 CONCEPTUAL MODELLING
In this section we show how a trainingscenario that
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