Game Development Reference
In-Depth Information
to the tool, thus making it more sensitive to
participants' decision-making styles.
decision support systems. Multi-Agent Systems
(MAS) is a sub-field of Artificial Intelligence that
provides both concepts and principles to build
complex systems involving multiple software
agents and mechanism to coordinate the inde-
pendent agent's behavior. There is no accepted
definition of “agent” in AI (Russell and Norvig,
1999). An agent can be considered as an entity
with goals, actions and domain knowledge, situ-
ated in an environment (Sterling, and Taveter,
2009). The design of complex programs like a
Multi-Agent System presents a paradigm where
systems are described as individual agents solving
problems by pursuing high-level goals. Figure 4
shows the architecture of the business simulator
from a MAS perspective.
The architecture designed enables us to use
different players, including both software agents
and human players. The different players par-
ticipate in a simulation in a step by step round
mode. In every step the player (software or hu-
man) receives the current state of the environment
and the player chooses the best decisions to make.
Then the round proceeds.
In this easy way, we can manage the simula-
tion where human and software agents participate
in the game. We have developed three kinds of
To access the descriptions and formulations
of the different variables, concepts, and
logical rules via hypertext techniques, link-
ing information generated by the Simulator
with the conceptual underpinnings and sci-
entific foundation in the Training Module.
Evolve the Training Module towards a
knowledge management system, allowing,
on the one hand, the participant to perform
a self-assessment of what they learned,
and, on the other, the instructor to track the
participants' learning progress.
Apply videogame technology to obtain
more realism in the simulator's business
This section describes how SIMBA can be used
for research in the application of Artificial Intel-
ligence (AI) to the area of business administra-
tion, which may provide us in the future with
new methodologies for intelligent business and
Figure 4. MAS perspective of the Business Simulator
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