12
X-Machines for Agent-Based Modeling: FLAME Perspectives
Step 6. Validity and verification of model: Involve validating and verifying results of simulation, to test if they are correct for conclusions
being drawn on hypotheses. At this step, review of the model correctness and result reliability can circle back to step one, by finding issues
or wrong assumptions in the initial model constructed.
It is important for developers and researchers to remember that a model is
not a goal of the experiment, but it is a process by which simulation will find
solution to the hypothesis being tested. Thus the model is only an enabler to
the process being investigated [59]. Figure 1.5 shows a flow chart of processes
involved when creating biological models. The figure highlights how modelers sometimes need to rework through initial model descriptions, to correct
models, after expert advice and results are obtained.
D E S I G N : U n d e r s t a n d m o d e l
I d e n t i f y t h e m e m o r y v a r i a b l e s o f t h e a g e n t .
I d e n t i f y t h e f u n c t i o n s t h e a g e n t d o e s .
I d e n t i f y t h e c o m m u n i c a t i o n t h e a g e n t d o e s w i t h o t h e r a g e n t s .
S i m u l a t e t h e m o d e l t o a l l o w t h e a g e n t s
t o i n t e r a c t .
T E S T I N G :
R e l e a s e m o d e l
u n d e r s t a n d i n g b e h a v i o u r .
S i m u l a t e d
r e s u l t s
i n v a l i d
S i m u l a t e d r e s u l t s
v a l i d a t e d
O b s e r v e b e h a v i o u r a l d a t a u s i n g g r a p h i c a l
t e c h n i q u e s a n d t o o l s .
R e a l e x p e r i m e n t a l
d a t a
I M P L E M E N T A T I O N :
FIGURE 1.5: Modeling process in biology simulations. cf. [107].
1.8.1 Research Examples
Natural Systems
Falling under area of swarm intelligence, ant colonies are extremely efficient
in finding shortest possible routes to food in minimum time. Proposed in
Dorigo’s PhD work [53], ant colony optimization algorithms can solve complex
X-Machines for Agent-Based Modeling: FLAME Perspectives
Step 6. Validity and verification of model: Involve validating and verifying results of simulation, to test if they are correct for conclusions
being drawn on hypotheses. At this step, review of the model correctness and result reliability can circle back to step one, by finding issues
or wrong assumptions in the initial model constructed.
It is important for developers and researchers to remember that a model is
not a goal of the experiment, but it is a process by which simulation will find
solution to the hypothesis being tested. Thus the model is only an enabler to
the process being investigated [59]. Figure 1.5 shows a flow chart of processes
involved when creating biological models. The figure highlights how modelers sometimes need to rework through initial model descriptions, to correct
models, after expert advice and results are obtained.
D E S I G N : U n d e r s t a n d m o d e l
I d e n t i f y t h e m e m o r y v a r i a b l e s o f t h e a g e n t .
I d e n t i f y t h e f u n c t i o n s t h e a g e n t d o e s .
I d e n t i f y t h e c o m m u n i c a t i o n t h e a g e n t d o e s w i t h o t h e r a g e n t s .
S i m u l a t e t h e m o d e l t o a l l o w t h e a g e n t s
t o i n t e r a c t .
T E S T I N G :
R e l e a s e m o d e l
u n d e r s t a n d i n g b e h a v i o u r .
S i m u l a t e d
r e s u l t s
i n v a l i d
S i m u l a t e d r e s u l t s
v a l i d a t e d
O b s e r v e b e h a v i o u r a l d a t a u s i n g g r a p h i c a l
t e c h n i q u e s a n d t o o l s .
R e a l e x p e r i m e n t a l
d a t a
I M P L E M E N T A T I O N :
FIGURE 1.5: Modeling process in biology simulations. cf. [107].
1.8.1 Research Examples
Natural Systems
Falling under area of swarm intelligence, ant colonies are extremely efficient
in finding shortest possible routes to food in minimum time. Proposed in
Dorigo’s PhD work [53], ant colony optimization algorithms can solve complex