Abstract
Multi-agent Simulation can be seen as simulated multi-agent systems
situated in a simulated environment. Thus, in simulations the modelled
environment should always be a first order object that is as carefully
developed as the agents themselves. This is especially true for evolutionary
simulation and simulation of adaptive multi-agent systems, as the
agents environment guides the selection and adaptation process. Also,
for the simulation of realistic agent behavior complex and valid
environmental models have to be tackled. Therefore, a modelling and
simulation system should provide appropriate means for representing
the environmental status, including spatial representations, and
dynamics. On the other side, simulation infrastructure should be
as simple as possible, as a modeler with domain expertise is usually
no computer scientist. He might neither be trained in dealing with
data structures and efficient algorithms, nor in traditional programming.
After going into the details of simulated environments for multi-agent
simulations, this paper shows how environments with different characteristics
can be represented in a particular modelling and simulation system,
named SeSAm, without asking too much from its users.
Users
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