CS 420/527 — Biologically Inspired Computation
NetLogo Simulation

Task Assignment

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view/download model file: TaskAssignment.nlogo

WHAT IS IT?

This model demonstrates the use of a Hopfield network to perform the Task Assignment Problem. See Flake (1998, ch. 18). Unfortunately, no further documentation is available at this time.

This section will give a general understanding of what the model is trying to show or explain.

HOW IT WORKS

This section will explain what rules the agents use to create the overall behavior of the model.

HOW TO USE IT

This section will explain how to use the model, including a description of each of the items in the interface tab.

THINGS TO NOTICE

This section will give some ideas of things for the user to notice while running the model.

THINGS TO TRY

This section will give some ideas of things for the user to try to do (move sliders, switches, etc.) with the model.

EXTENDING THE MODEL

This section will give some ideas of things to add or change in the procedures tab to make the model more complicated, detailed, accurate, etc.

NETLOGO FEATURES

This section will point out any especially interesting or unusual features of NetLogo that the model makes use of, particularly in the Procedures tab. It might also point out places where workarounds were needed because of missing features.

RELATED MODELS

This section will give the names of models in the NetLogo Models Library or elsewhere which are of related interest.

CREDITS AND REFERENCES

This model is a reimplementation of the Task Assignment Hopfield Network in Flake, G. (1998), The Computational Beauty of Nature. Implemented by B. J. MacLennan, Sept. 30, 2008.

To refer to this model in academic publications, please use: MacLennan, B.J. (2008). NetLogo TaskAssignment model. http://www.cs.utk.edu/~mclennan. Dept. of Electrical Engineering & Computer Science, Univ. of Tennessee, Knoxville.

PROCEDURES

globals [
 width
 height
 num-cells
 weight-array
 bias-vector
 test-data
 est-cost
]

patches-own [
 state
 new-state
 local-field
 activity
]

to setup
 set width world-width
set height world-height
set num-cells width * height
 set weight-array n-values num-cells [ weight-row ? ]
 randomize-state
 set-defaults
end
to set-defaults
 set gain 0.5
set scale 0.5
set test-data
 [ 10 5 4 6 5 1
6 4 9 7 3 2
1 8 3 6 4 6
5 3 7 2 1 4
3 2 5 6 8 7
7 6 4 1 3 2 ]
 set-test-data
end
to set-test-data
 set bias-vector compute-bias-vector test-data
 ask patches [
 set plabel-color green
set plabel item (cell-num pxcor pycor) test-data
 ]
end
to-report compute-bias-vector [data]
 let min-cost min data
 let max-cost max data
 let avg-cost mean data
 report map [ scale * (? - avg-cost) / (max-cost - min-cost) + 2 ] data
end
to-report weight-row [i]
 report n-values num-cells [ ifelse-value (i = ?) [0] [ weight-val i ? ] ]
end
to-report weight-val [i j]
 let ix floor (i / height)
 let iy i mod height
 let jx floor (j / height)
 let jy j mod height
 ifelse ix = jx or iy = jy
 [ report -2 ]
 [ report 0 ]
end
to randomize-state
 ask patches [
 set new-state -0.1 + random-float 0.2
update-patch-state
]
end
to start-test
 randomize-state
 clear-all-plots
end
to go
 ask patches [ compute-patch-state ]
 ask patches [ update-patch-state ]
 plot-energy
end
to compute-patch-state
 let index cell-num pxcor pycor
set local-field sum map [ (weight-value index ?) * cell ? ] n-values num-cells [?]
 set new-state state + delta-t * (local-field + (item index bias-vector) - state / tau)
end
to update-patch-state
 set state new-state
 set activity sigmoid state
 set pcolor scale-color red activity 1.0 0.0
end
to-report sigmoid [x]
 report 1 / (1 + exp (- gain * x))
end
to-report cell [p]
 report [activity] of patch (floor (p / height)) (p mod height)
end
to-report cell-num [x y]
 report x * height + y
end
to-report weight-value [p q]
 report item q (item p weight-array)
end
to plot-energy
 set-current-plot "Average Cell Energy"
plot (- sum [ state * local-field ] of patches / (num-cells ^ 2))
 let activities n-values num-cells [ cell ? ]
 set est-cost sum (map [?1 * threshold 0.9 ?2] test-data activities) ; / (sum activities) 
set-current-plot "Estimated Rate"
plot est-cost
end
to-report threshold [theta x]
 report ifelse-value (x < theta) [0] [x]
end