Biology Reference
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d.
Objectives. If adaptive traits explicitly act to increase some measure of
the individual's success at meeting some objective, what exactly is that
objective and how is it measured?
e.
Learning. Many individuals or agents (but also organizations and insti-
tutions) change their adaptive traits over time as a consequence of their
experience? If so, how?
f.
Prediction. Prediction is fundamental to successful decision-making; if an
agent's adaptive traits or learning procedures are based on estimating future
consequences of decisions, how do agents predict the future conditions
(either environmental or internal) they will experience?
g.
Sensing. What internal and environmental state variables are individuals
assumed to sense and consider in their decisions?
h.
Interaction. What kinds of interactions among agents are assumed?
i.
Stochasticity. What processes are modeled by assuming they are random
or partly random?
j.
Collectives. Do the individuals form or belong to aggregations that affect,
and are affected by, the individuals?
k.
Observation. What data are collected from the ABM for testing, under-
standing, and analyzing it, and how and when are they collected?
5.
Initialization
Questions: What is the initial state of the model world, i.e., at time t = 0 of a
simulation run? In detail, how many entities of what type are there initially,
and what are the exact values of their state variables (or how were they set
stochastically)? Is initialization always the same, or is it allowed to vary among
simulations?Are the initial values chosen arbitrarily or based on data? References
to those data should be provided.
6.
Input data
Question: Does the model use input from external sources such as data files or
other models to represent processes that change over time?
7.
Submodels
Questions: What, in detail, are the submodels that represent the processes listed
in “Process overview and scheduling”? What are the model parameters, their
dimensions, and reference values? How were submodels designed or chosen,
and how were they parameterized and then tested?
4.5
COMMENTS FOR INSTRUCTORS
While ABMs have provided rich insights into multiple research areas for many
decades, they have not traditionally been involved in the classroom. As a conclusion
to this chapter, we take a fewmoments to explore some of ways in which explorations
in agent-based modeling might benefit students.
ABMs contain easily explained concepts, and provide a framework to allow stu-
dents to explore new tools and subjects. Through ABM creation and exploration, our
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