Conclusions and outlook - Modeling and Simulation of Complex Systems - page 167

11 Conclusions and outlook
The development, analysis and evaluation of complex systems requires
moreandmoretheuseofmodelingandsimulation,asitisoften
impossible to do otherwise. Often microscopic modeling approaches
like agent-based modeling and simulation are used for representing
such complex systems. Despite widespread use in many application
areas, the foundations of agent-based modeling and simulation are
much less profound than in other established modeling paradigms.
With special emphasis on agent-based modeling and simulation, this
thesis aims at two goals. Firstly, improving effectivity and eciency
of model development and secondly, improving effectivity of model
execution.
11.1 Summary
Based on extensive analysis of basics and related work in the area of
agent-based modeling and simulation, this thesis identifies the need
for a reference model for agent-based modeling and simulation. The
newly developed General Reference Model for Agent-based Modeling
and Simulation (GRAMS) defines on a generic level components and
structure of agent-based models as well as the simulation of such
models. The GRAMS reference model considers the macro-level as
well as the micro-level of agent-based models. The macro-level specifies
the simulation time, the simulated environment in which all agents
are acting and constraints limiting the agents possibilities to act.
On the micro-level, the GRAMS reference model defines structure
and behavior of agents. An agent is characterized by a set of attributes,
may perceive its environment by a set of sensors and may interact
within the environment by means of effectors. Sensors and effectors