1. modelling biological & physical systems
Simon Lynch

2. biological systems simple (eg: cell growth) swarming & flocking
evolution
ecosystems

3. physical systems examples... atomic (sub-molecular) small & fast
molecular (fluid particles, etc)
erosion big & slow
continental movement
weather systems lots to
climate change model

4. moths, fires, etc

5. the problem complexity #1 – scale spatial - too big or too small
temporal - too fast or too slow
logical - too many objects / parts

6. the problem complexity #2 – interactivity
lots of interaction between parts
lots of interdependence between parts
emergent behaviour
eg: cellular automata

7. computational modelling
spreadsheets, etc?
ok for some v.simple systems but – no observation
programming languages
ok but – big effort needed (& lots of time)
special modelling tools
eg: NetLogo (ccl.northwestern.edu/netlogo/)
good & quick but some limitations

8. sample NetLogo code from NetLogo sample model library "Moths" model
to move-thru-field ;; turtle procedure
ifelse (light-level <= ( 1 / (10 * sensitivity) ))
[ ;; if there is no detectable light move randomly
rt flutter-amount 45 ]
[ ifelse (random 25 = 0)
;; add some additional randomness to movement
[ rt flutter-amount 60 ]
[ ;; turn toward the brightest light
maximize
;; if light ahead below sensitivity threshold
;; head to it otherwise move randomly
ifelse ( [light-level] of patch-ahead 1 / light-level
> ( / (10 * sensitivity) ) )
[ lt ( direction * turn-angle ) ]
[ rt flutter-amount ] ]]
if not can-move? 1
[ maximize ]
fd 1
end
from NetLogo sample model library
"Moths" model