请问 我现在希望设计海龟死后他的财产可以以一定的比例留给后代。这些海龟如果代表的是穷人则它死后(年龄大预期值)会生出3个孩子,其生前的财产的90%均分给其孩子。若海龟是富裕的,其死后有随机1~2个孩子,财产已70%均分。请问大家如果加到下述程序中怎么实现- G) A" B9 M+ |% W8 c
globals
2 Y- A! x8 w, w[
1 A( \9 X7 ^- \3 q! F0 Z3 h max-grain
" [9 x1 c# N3 z/ ?# g+ R% b; q% O% w
]' W: ]6 \4 C1 f, l
0 s9 \% K: Z. y" v' J/ l3 s1 N& `0 m( opatches-own
+ c: p1 V/ s% o# L[
# P; m( {( Q9 U u3 l0 m q grain-here & |$ G" k% Z* o1 a6 H
max-grain-here
1 o- |6 G+ `5 x7 x]7 x5 ^; ?- E4 q+ S7 R
9 D' e& v$ X4 X0 J2 |
turtles-own
& T; i+ i O$ ` P& j5 ][: K/ s! M! \$ s3 N/ o
age ( {* z+ f4 [, n: k8 U% n% b2 R. g
wealth $ Z$ r8 T5 J( j
life-expectancy
# o! Z& x% j: | metabolism # h; l: S( H+ D" C% e+ k) ~. I
vision
5 \8 L( C2 L- q; y- s, I, | inherited
2 z% E |* Q; N" ^]
/ i5 ?- W( A! [ t/ i5 V- R; Y3 X* C5 x' x4 u, P
" X7 p/ W8 t9 {# V( t4 e
to setup
7 }4 X+ C3 g9 ]$ X* s* j ca8 J1 j/ d' j& H, ^5 S3 I
set max-grain 503 @" u1 U" _/ k& k1 e; `7 B
setup-patches, }% J9 H7 s) ^# e
setup-turtles/ [ W# p" A1 Y/ B" y
setup-plots- D0 V- W* l" \* Y2 c
update-plots$ q, n9 l! v4 p, X
end1 O8 e7 f; s. K- ^1 G* D9 R3 Q: \8 m4 W
to setup-patches* G9 u w1 q: B) U3 e
ask patches
& W q2 ]4 H ]; V8 P [ set max-grain-here 0. m* n2 O% U# [8 z# l* V) [
if (random-float 100.0) <= percent-best-land
& t5 H" [3 F; d( B a0 s# A [ set max-grain-here max-grain
. p7 S u- H) R2 T( g: q set grain-here max-grain-here ] ]- W% ^, r) ]0 \ x
repeat 58 K. a- x8 M9 E2 {1 Z
[ ask patches with [max-grain-here != 0]
7 y3 u( t+ J1 A& H) x% j [ set grain-here max-grain-here ]
7 z0 f5 s! }, N: _; u diffuse grain-here 0.5 ]* J8 X$ H$ ]' k7 F
repeat 10* z4 j$ c3 b! O2 `6 N# O* c
[ diffuse grain-here 0.5] : L/ V: w5 ^; @9 _8 G
ask patches
2 {) X: G. }( Y/ [5 F+ y1 G [ set grain-here floor grain-here 6 N/ q0 J9 {2 e- f
set max-grain-here grain-here
6 T) o: j9 O! v. Z recolor-patch ]
7 k- W. f v$ \$ T. Cend0 I1 X1 d) u% _+ j, {: U
to recolor-patch
% Q* Z- l& v- B0 g& \: n set pcolor scale-color sky grain-here 0 max-grain* c+ c8 L+ F: B; i
end1 b) n1 ~1 V9 }0 k- M! h# J. X2 u" |
to setup-turtles! L$ p$ s `& ~& u
set-default-shape turtles "person"7 l0 c, R% ]6 n* A
crt num-people* h$ X$ o& h8 R. s( c1 @( I% {
[ move-to one-of patches ) ~% Y/ v. h5 m9 B* [
set size 1.5
; N: L' f1 x N) h set-initial-turtle-vars-age% G- {4 j" z/ w+ j- I& V
set-initial-turtle-vars-wealth/ T* W9 U# J) U4 ~* j6 g
set age random life-expectancy ]
2 S: S* f& k0 ^) f7 z3 k recolor-turtles
~1 b: Y& Q6 nend) j% V! k1 L8 Q) n0 W5 B; Y3 g6 i2 B) Q
' n! y7 w6 X: Q/ ]! qto set-initial-turtle-vars-age
* D5 n6 }2 i0 Q( A* k; E. W7 g let max-wealth max [wealth] of turtles
/ m( F- d/ J& f7 F, e1 t+ v ) t1 Z5 [; ]( g2 i1 e0 T
ifelse (wealth <= max-wealth / 3)
; P* b) \, h* s- m, y* x0 [ [ set color red - E; E+ [, ]- o# u/ t8 }
set age 0% U) `# n) _" e) a$ F
face one-of neighbors4
0 u- `) B5 `3 ^4 f" ~ set life-expectancy life-expectancy-min +
* Y- q- z& o, u" H# [# F random life-expectancy-max # c _, [: I& S( A& f/ y& P
set metabolism random 1 + metabolism-low
- G, v) I* A% U set wealth metabolism + random 30! i( k/ L% b6 s1 P
set vision 1 + random max-vision
# |, H& K+ y% n7 L! n$ b+ `: f1 q' X set wealth wealth + Wealth-inherited-low ]
. F/ F7 ~4 Z- R$ Z( V [ ifelse (wealth <= (max-wealth * 2 / 3))) `) ~( \1 e; A0 g
[ set color yellow
, j+ B. ?, q# Y+ W set age 06 b3 t, ^8 y5 z s R* N1 g
face one-of neighbors4 : C# }3 ^2 ~3 o, o1 T
set life-expectancy life-expectancy-min +8 G$ t, x4 s- i9 f
random life-expectancy-max + 11 H7 H) X; X$ u: j
set metabolism 1 + random metabolism-mid* s2 M! t1 P6 r' O: {
set wealth metabolism + random 30
% A- m. l/ B7 P! l6 @# j set vision 3 + random max-vision
7 z, x( [' s; ]5 x; e; a& I. g% G set wealth wealth + Wealth-inherited-mid]% ?+ X9 G5 ^0 `$ j3 W
[ set color green
7 K" J+ C7 h! X& J8 U) Z4 I- q- ^ set age 01 V! X% h9 Y' j7 Y: O2 Q8 n
face one-of neighbors4
Q7 p! z4 j ]2 G, v set life-expectancy life-expectancy-min +: k+ l6 F/ s, y4 K Z) B* B
random life-expectancy-max + 2) p/ f# F( ]* K6 P: c/ Y& q. ^
set metabolism 2 + random metabolism-up
4 |. Y/ k9 j I3 j3 B set wealth metabolism + random 303 p1 B; I2 a: Z, A' g4 Q. ^
set vision 3 + random max-vision, ~* v: c" ~2 G' H
set wealth wealth + Wealth-inherited-up ] ] 7 G5 s! N* ?! X8 P- w
; b* l- r2 j# ]* G4 B& T# Xend
+ m& l% _. X1 A: \to set-initial-turtle-vars-wealth
* j& i# B k+ s+ W6 w8 p let max-wealth max [wealth] of turtles5 X# @0 v5 E9 D" u/ W% Z! M% \7 z2 N
set age 0
# M% w* v/ m9 u face one-of neighbors4
- s$ k5 u* ^. p set life-expectancy life-expectancy-min +
/ r4 ?& A/ n+ f3 J W' w random life-expectancy-max
. D% F" A2 x2 E) U+ i set metabolism 1 + random metabolism-up
! y d) {# X. J. I set wealth metabolism + random 30# V3 O/ T- s$ j- ^
set vision 1 + random max-vision
3 d: g7 X; r; F" w; ^4 X5 I9 kend, \; k- _) w! ~ m( w/ d" E
to redistribution
# m. K) I# X5 J* m, {# Xlet max-wealth max [wealth] of turtles9 g8 ^7 m9 ]3 J$ N p
let min-wealth min [wealth] of turtles4 a- |8 ]" [3 V1 k
if (wealth <= max-wealth / 3)+ J$ e7 R1 @, c# g" U6 H+ Q4 }; z
[set wealth wealth + Low-income-protection ]
) B |/ ?$ C9 S: t5 Wend
: u4 U7 X+ i+ k( a J
; [* g3 [9 i* Z0 G; hto recolor-turtles
0 k/ F" R" M1 L. E8 q: n6 O/ J1 L let max-wealth max [wealth] of turtles+ K5 U$ ]8 g) }. d" n; I! I3 ~
ask turtles; Y( V7 Z9 O) L! F; s7 f4 n
[ ifelse (wealth <= max-wealth / 3)
% i( h8 l. X( w' k+ v [ set color red ]
% \" ?1 m9 o: @ [ ifelse (wealth <= (max-wealth * 2 / 3))
. C6 s* q; @( r# T" A [ set color yellow ]
) w) V8 Y# c0 K2 z7 [9 H* ^ [ set color green ] ] ], m' l! @3 g* w
ask turtles [ifelse show-wealth?/ j9 A) x2 a t' H& p
[ set label wealth ]
4 a( [7 F5 y5 W, J& l* A5 J V [ set label "" ]]" J6 |6 n! E; p$ K* K6 K3 F
end/ x! e% @# _. M+ C
6 \6 t- ]0 F( Y( n4 \" I
to go
9 Q+ p" L, h9 I, v8 {% g& |4 S: R: Q ask turtles
& K% {/ s3 {+ m [ turn-towards-grain ]
) M( J* {! L, t$ s harvest
1 ~. s4 P) t6 Y1 y0 a. _ ask turtles
: t3 p/ T. e+ y' ~. U0 h/ X. ? [ move-eat-age-die ]
7 J$ G' T' q0 j; Q, b recolor-turtles1 Y% M8 g3 @+ ]4 i a' b* _6 m) P
if ticks mod grain-growth-interval = 0
0 r/ p- X6 S; F3 ` [ ask patches [ grow-grain ] ]
: ] V- x4 k8 H( a! l: h5 g $ b9 s3 X# S5 H, d4 v+ ~
if ticks mod 11 = 0
' H7 T) S8 E# _* K7 @& W [ask turtles+ E% a$ z2 J3 H5 Z% |: u
[ redistribution ]]9 Z" C+ Y7 h* [7 H$ ], }# a2 x
if ticks mod 5 = 0) t" j% k/ i8 u2 F+ \3 L+ e* \
[ask turtles i# z% }8 Y' a" K) T Q
[ visions ]]% W3 g- o( g: v7 n$ {
tick
; M+ ^+ C2 T7 x update-plots$ R" g% h2 Z; c+ O
end4 X, E% `) V0 Q. ~' A* A
to visions
- Y! y. g4 W0 P- k Y set vision vision + 1
2 L8 V- U6 f7 y8 J Gend" G/ u3 t$ x; c1 N1 R# d$ P4 d
- _2 @( F* f" x& t- J& x& m4 x' J: p: s/ I- R0 e
# i7 i5 P- ]- Z/ B6 _/ }/ _to turn-towards-grain
7 z p* _5 g# x7 x5 x; w7 P set heading 0
; D) j8 m g" @# z let best-direction 0
4 v! _! c0 w/ D let best-amount grain-ahead# ?% Y" r' Q! \6 A4 n
set heading 90
: F/ A, Q2 N' s$ y if (grain-ahead > best-amount) J0 A/ b: Z' {2 m& I, y9 w
[ set best-direction 90. q6 _$ K" n0 j* |6 w) ]9 `" Z
set best-amount grain-ahead ]6 X3 Z T" x3 a8 e) W U* @ |
set heading 180
5 M3 E- u' A5 h$ {7 T if (grain-ahead > best-amount)
7 ~/ N6 j. W4 s& j3 V3 f( b [ set best-direction 1804 }+ B, ~6 e3 O2 Y; p) I
set best-amount grain-ahead ]
4 K8 S+ K& `# O0 y7 v# E1 @( N- y set heading 2703 m& D4 d& @$ y- B( F5 l( e% n, H/ g
if (grain-ahead > best-amount)
$ c7 c1 z6 N% J7 c/ \ [ set best-direction 270
, `0 P! e5 [% k; |4 [! A( \ set best-amount grain-ahead ]/ ?4 Y5 @0 @# T. s; E
set heading best-direction5 T: l/ ]$ H- `( u
end: n3 D- q; x8 v/ f. |
. Y' |& w \; C! F) q- p) C4 w
% K, u! N; v) `8 }& ?
to-report grain-ahead % y1 M- W/ H' K5 d4 Y% ~7 C! Q- s
let total 0
% j6 w3 g1 y: ~6 g! u6 } let how-far 13 S6 H# t! |6 \/ @. @3 t
repeat vision
4 t; }! \6 \: C; G0 p1 _ [ set total total + [grain-here] of patch-ahead how-far t) L4 ^! q9 c8 |/ w) m* e# }
set how-far how-far + 1 ]
0 c1 o: l9 D3 {9 d5 K report total
5 U/ o- _; i! D, Q# Y7 Bend: P: V! N! d1 L6 D, t" c, j" Y
! v6 T5 n' A. a) @( B' V& X
to grow-grain 9 |6 `: n2 a+ t- {# F* d e
if (grain-here < max-grain-here)! T: B7 d" n& X; i$ o( ^" K3 W" a
[ set grain-here grain-here + num-grain-grown
* G! W- Z; L" O* x) x if (grain-here > max-grain-here)
8 i0 k1 f, @: N6 P: t1 `1 j [ set grain-here max-grain-here ]/ }0 ?4 N( z( z5 ~7 Q; n
recolor-patch ]
: q0 e' I8 v7 O# X% _7 qend
" o* I: |# A! Y' I' Tto harvest5 a. r e3 |+ W% v
ask turtles
! X8 g# N- Q8 l6 m" W [ set wealth floor (wealth + (grain-here / (count turtles-here))) ]9 V$ N) x: s& d0 c* b5 f
ask turtles' z5 E3 o+ G" l6 Z' m/ g
[ set grain-here 0% W5 k2 B- U3 e8 v2 B, M) F( G
recolor-patch ]& S( y8 r; L8 m1 I
" x6 j0 k& ^) M3 [end
& Q& B' _) Q$ @9 ]) p' j- j8 o7 ~8 m* C3 k# r: f
to move-eat-age-die
( ~8 C# r6 P7 Z% d" ?5 @8 ~ fd 1% E" X: U' p' Y- n8 |
set wealth (wealth - metabolism)7 ~" H' t2 ~: a. _. } S7 d3 @
set age (age + 1)+ S7 Y+ p o3 `6 h3 u2 p5 R2 `
if (age >= life-expectancy)
9 A* p* J8 f8 r* m+ C' R [ set-initial-turtle-vars-age ]
8 n6 f. M8 b- D d' K, y if (wealth < 0)
' W4 r8 i9 e+ P$ ^) z. [' Q; Q [ set-initial-turtle-vars-wealth ]2 b: K& s" M/ {2 j9 D9 U9 D: u
* R# h% p2 }) [2 Kend
* v4 [& b1 Y0 t! G' i0 Q* G* S
2 w/ \+ ]& ~6 s5 c4 X$ y8 F) s+ r; _8 j, L$ @' z! k. C
to setup-plots
. R1 x- ^! f) p! y set-current-plot "Class Plot"
$ c- c+ |4 W% |5 J R set-plot-y-range 0 num-people
8 G" I2 r" u6 v; k4 F set-current-plot "Class Histogram"
. [( o' E7 K! g7 L6 {" l% o set-plot-y-range 0 num-people
& @/ U, k7 G4 A& W8 pend! v- A8 R5 W @
! V( T1 v: U1 \2 r5 eto update-plots& Q9 M! M6 S- K6 Y/ ~1 H2 j# i/ v
update-class-plot
4 L: M- f" _$ L3 K update-class-histogram
4 P2 c5 @- K4 g S" @2 r2 T7 `, H update-lorenz-and-gini-plots
: p% u6 W4 B, J# }* Q/ O! hend/ S) ~) c* A3 \
! ?) y5 M5 y4 X4 o/ L2 `to update-class-plot
0 x+ r& ~& {0 K: C- c set-current-plot "Class Plot"
5 |5 X7 b6 Y) s3 S, o9 t set-current-plot-pen "low"
3 u) I6 V* [2 D plot count turtles with [color = red]6 Z* D* B, C0 L6 p$ \. c e
set-current-plot-pen "mid"
* s5 t; O( [0 p" s4 | plot count turtles with [color = yellow]. Y% Y% q3 M6 \
set-current-plot-pen "up"$ A4 Z- {( v2 o6 K+ F- z t' x
plot count turtles with [color = green]
" Q( S! M' V1 S9 aend
- t0 |! _9 R: b- z/ e8 P3 [9 N; I! k2 O
to update-class-histogram
7 D9 N* ]# l2 b. Z) P8 u" L4 A6 i set-current-plot "Class Histogram"
4 n, y. p1 ]# C$ }* Q9 Y, a plot-pen-reset
3 N0 S* \& n, j/ |$ e2 p7 ? set-plot-pen-color red
7 A! k. t5 \* C/ N plot count turtles with [color = red]6 x+ d+ P' }* O- [
set-plot-pen-color yellow
9 G0 O! P1 O, I1 m/ v plot count turtles with [color = yellow]5 b$ \# K) i3 ?) f
set-plot-pen-color green2 [4 [9 c# n$ B& o$ h
plot count turtles with [color = green]
, J* ]6 g+ t* E* A4 [9 Fend
# B* F! f! u z- Fto update-lorenz-and-gini-plots/ y* W3 M# v' d% I5 p1 x
set-current-plot "Lorenz Curve"/ F) H3 h# _7 q+ H, N' K0 Y ]& @
clear-plot
F7 |- V+ Y0 q9 ^8 T) Q$ o
1 A' X% X0 d7 p9 N1 Q+ U, i set-current-plot-pen "equal") P; C2 O$ w' x" n* z( L
plot 0
( e' c% C% ~2 K' b. n) r$ ^7 j plot 1000 e) b9 ^7 m" ^- f& u
) W/ |* \/ K3 M4 Y- x3 B set-current-plot-pen "lorenz": H& o8 J i, V; Z& V0 \
set-plot-pen-interval 100 / num-people5 s2 ^: B; ~( s3 O j
plot 0
& j' z- x6 N& ]% K- i- G5 B- S
! i2 K+ E/ ?, z( K* c let sorted-wealths sort [wealth] of turtles% d$ l" ^! [! _; [. m
let total-wealth sum sorted-wealths
, P: D) ^, L' H9 j+ d) o let wealth-sum-so-far 0
# Z/ A0 W7 K. e& M3 D let index 0
3 E4 y5 y" ?7 n k/ H let gini-index-reserve 0
' w. ^+ \( K7 F. y( x3 ~. S; W) T* A, D
repeat num-people [' U- Q: X" `. w8 ?
set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths): O5 j/ w: n# H9 D& r$ c/ _
plot (wealth-sum-so-far / total-wealth) * 100
) z, `3 C" ?8 d set index (index + 1)
/ R) U6 i( O& g set gini-index-reserve. @& E* |# l! v1 W1 ?
gini-index-reserve +
7 G' e/ r. W. A! W9 f4 v (index / num-people) -
+ c& V3 Y2 x1 [" E: | (wealth-sum-so-far / total-wealth)
6 F+ u' y9 E9 W7 [ ]7 O. C7 x% Z; j3 K4 s' d
; o; T6 M3 e8 I+ i, r
set-current-plot "Gini-Index v. Time"
( b4 @! d8 ?3 L* Y: Q( u- U1 Q plot (gini-index-reserve / num-people) / area-of-equality-triangle
* l. r4 Z; b4 a3 G& l( g& z2 jend& G6 _. E0 k4 Z3 ^: f
to-report area-of-equality-triangle
. L- A/ t9 I; \. t$ w; F report (num-people * (num-people - 1) / 2) / (num-people ^ 2)
0 I2 h) [& F! c* ]5 _end |