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
0 C: ~+ k" `% ]0 j& h. f5 zglobals
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max-grain
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8 [: {& E: W3 l6 [
patches-own
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grain-here
5 D+ ?, v, L5 x/ Z7 {- h max-grain-here ) {( Q `6 E( h; @. z9 Y( F
]" z+ |# [) g% z5 P3 \
4 k2 ] y5 k5 f& m1 Y9 Eturtles-own
/ U Y0 B. U F0 l[
7 W# a! t; _9 p. O: b age & S4 g7 |6 R- M8 N$ ~
wealth
8 s% P. A9 I" n- t) @ life-expectancy / {: c6 x/ z1 o1 u% w/ \: a
metabolism
& ]5 `- k* w. H6 C7 @" ]% G9 [# V- m vision/ |& D' h) X0 S
inherited
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5 V4 Z0 F' t( @) P8 Z" |1 Hto setup7 [' Z$ i+ g8 }# J! ~8 ~9 O5 f
ca1 R, W; o5 f3 s9 S. B1 `
set max-grain 505 I7 z6 U2 n/ p( |8 f& S" P
setup-patches
# p) C, S" d4 ~" I8 l; M2 M) j setup-turtles5 E _& D5 Q- y9 _
setup-plots- d9 b; r* @# q5 @4 S: L- S
update-plots4 f! ? k, `. _1 [
end
# m' ~0 Y( q: _+ ?; G) B; v7 ^to setup-patches
# L+ ~+ h3 |% ^* y+ v& K ask patches% a: j1 q5 Z4 j4 v8 W4 M$ Q
[ set max-grain-here 0
- o. e/ G$ z, w8 w4 ~: B& h if (random-float 100.0) <= percent-best-land- X; ~5 V. J+ F; I5 A2 L
[ set max-grain-here max-grain
2 M4 j4 u' O) ~! F, l set grain-here max-grain-here ] ]/ k8 S# N% L {
repeat 5
6 U7 ~9 A0 i% }$ [2 I/ r% m @* Q [ ask patches with [max-grain-here != 0]% O$ f/ `: y/ B- C# o$ O x9 i3 M @
[ set grain-here max-grain-here ]
, t# b7 d+ S; @, {: y6 X diffuse grain-here 0.5 ]; Q f2 T! V% I9 S0 T
repeat 10' c4 `0 ]; a. J* p
[ diffuse grain-here 0.5]
$ C r) j s& @3 p2 {' I ask patches
1 k$ l ]# J0 y( {5 `# U [ set grain-here floor grain-here
* d* q5 ^& P8 L: v) a2 j set max-grain-here grain-here
7 r" `' ^) k( f; a recolor-patch ]
9 K% n3 c6 Y' S- ^$ N2 P, Oend
5 ?( l8 i# ~" [: v9 @9 Uto recolor-patch ) l$ x+ o1 b5 S- M1 }
set pcolor scale-color sky grain-here 0 max-grain
2 v% }' e3 _2 D( r3 B5 Qend
: [! E4 v5 L0 g$ m7 V5 ~) u7 Pto setup-turtles& U: F! w8 R7 l
set-default-shape turtles "person"! R# {, m; l" l! R% ]" n
crt num-people
) [/ Z5 L4 U- x [ move-to one-of patches
0 f! B( t# u: r5 O7 m set size 1.5
) i E3 P7 Y q1 i7 A6 b8 j0 R7 ~ set-initial-turtle-vars-age
+ J; u* ?0 k( Y* _7 I9 Z( i set-initial-turtle-vars-wealth
, m4 `) d a& z5 n# D) B' S7 | set age random life-expectancy ]
/ W4 g% ^8 v+ H recolor-turtles. T8 Q& w; r* |8 s. ?
end
2 V+ _$ g2 v( b/ G' X4 @6 V. o" @9 i z$ {9 v: }6 R) O5 I
to set-initial-turtle-vars-age
3 F% e2 g, c/ I# |! c5 W& r let max-wealth max [wealth] of turtles
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) H; V9 V' T. m4 Y7 R* s- \ ifelse (wealth <= max-wealth / 3)
$ r, ]6 _3 U W. z0 a( O0 [ [ set color red * B; |6 q2 `, a' n# y
set age 0
: K0 ~& g9 a1 m! M- W x face one-of neighbors4 6 T6 d4 m7 N5 V# U
set life-expectancy life-expectancy-min +
2 N& J# }" J, ^+ z/ d! i3 ]! J2 E random life-expectancy-max
8 B8 }0 H: h2 y n set metabolism random 1 + metabolism-low
0 K2 B# q# f8 |- Q3 W set wealth metabolism + random 30% v" _: Z. s" O- J. O: j5 b
set vision 1 + random max-vision
5 o9 f# d3 K+ g+ V7 Y6 ?3 Q: `# K4 y set wealth wealth + Wealth-inherited-low ]7 a4 M4 b. G* ]
[ ifelse (wealth <= (max-wealth * 2 / 3))3 v0 @4 ~1 t3 O9 t
[ set color yellow
/ t# B y: o8 d9 p9 l set age 0* y M1 x6 D1 w4 |; L& G3 f
face one-of neighbors4 " [ ?/ p# v2 k5 i& x( I
set life-expectancy life-expectancy-min +" O- W* @) ~' r1 f7 m" b) H
random life-expectancy-max + 1: C5 c7 }8 i4 H) V$ y
set metabolism 1 + random metabolism-mid
3 [6 D0 ~4 E2 M set wealth metabolism + random 30
% G4 P1 r) p7 B( _5 O3 C set vision 3 + random max-vision
; i* j6 j( t( `, V7 [6 ? set wealth wealth + Wealth-inherited-mid]' G6 F% p3 E! a# `5 w \
[ set color green
7 T3 T/ g! r3 R$ i6 f# ~ set age 0( q( u" u2 Y+ c. B( W1 a7 V
face one-of neighbors4
5 x& Q- ^' D! E* r1 u+ h8 v+ \. D9 F set life-expectancy life-expectancy-min +
" r1 s/ U9 s. r+ S! g random life-expectancy-max + 2" K1 N0 J. [ _3 E1 q' O
set metabolism 2 + random metabolism-up
' m2 {5 d6 y. }9 b% @! R( _! z( z& P set wealth metabolism + random 30, h2 n& H1 K* u. I3 I: G- Z, l; j B
set vision 3 + random max-vision
2 m3 v9 f `$ H9 Q set wealth wealth + Wealth-inherited-up ] ]
& m" S x' F4 g# \8 {( v9 @' M
# u! d2 J/ u, V. Vend& E( f9 x7 Y' O
to set-initial-turtle-vars-wealth
) ]6 x- |0 i0 g" Y/ y let max-wealth max [wealth] of turtles- ]* f3 ?# g' O+ e
set age 0
. G8 X2 N! G: k; F2 H/ t2 g- \ face one-of neighbors4
; A! z G2 l: ?1 c+ R set life-expectancy life-expectancy-min +
- J; c. }) H: z random life-expectancy-max
' Q0 @' Z( ]. o1 J/ T set metabolism 1 + random metabolism-up, r ] n5 ]2 x @4 J
set wealth metabolism + random 30: G; w* x, N5 d& i4 t
set vision 1 + random max-vision , r0 z* `, S' x# ]8 ~
end
! y9 H8 L/ f! G! {" y( t9 wto redistribution) g4 D+ s/ ]# G+ h: `) b; ^- b. `/ t
let max-wealth max [wealth] of turtles
$ I7 s4 z, Z1 Z5 {% c, g- `/ olet min-wealth min [wealth] of turtles3 X7 z) D. V' H; D5 N- f5 L
if (wealth <= max-wealth / 3)
1 P! w" x; J( G4 t- w [set wealth wealth + Low-income-protection ]
: ]+ x( l8 u3 Z" gend% o7 f- l. H1 K' G
/ b% U' k' G+ k; {7 pto recolor-turtles
2 i# E' t1 b% F u! f8 s let max-wealth max [wealth] of turtles Z9 [6 S, e: [1 m
ask turtles
. Y+ G: g% D& w- M [ ifelse (wealth <= max-wealth / 3)
/ L* K9 Z: |5 c9 y [ set color red ]1 n/ [. ^3 Z9 i
[ ifelse (wealth <= (max-wealth * 2 / 3))
2 l' N g5 ~; u+ Q i# V2 J& H [ set color yellow ]* ~" l7 H s$ C# D
[ set color green ] ] ]
! [7 W$ ~0 q" b$ w# R2 x9 k% u ask turtles [ifelse show-wealth?: D/ R9 [7 T$ A
[ set label wealth ]- b' z% M; K$ u2 ?1 I$ E
[ set label "" ]] @# [& O. e! [+ g
end* u* w* ]1 M4 M& E3 a
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to go. |4 g) A+ f" s ` k W
ask turtles) p5 h/ s, F* m! M0 D# ]! l
[ turn-towards-grain ] % U. q% n- W& P9 k( T3 D
harvest* @0 B6 X* K. }+ k, k( f) i
ask turtles
; W/ R- [. D5 M) g- [* ^ [ move-eat-age-die ]
% v$ o3 }" y. t5 k! F recolor-turtles" a6 E8 T, `: b
if ticks mod grain-growth-interval = 0" [$ R* R1 J( g% F8 x* D6 u
[ ask patches [ grow-grain ] ]
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if ticks mod 11 = 08 p. X4 D& g1 L7 W2 x' t" D
[ask turtles
5 Z, T- T7 |: k; `9 ^ [ redistribution ]]
! n' z6 |; m* O0 p N$ e; o if ticks mod 5 = 0
. b* X6 ]' ^0 }5 i3 k. I- {4 U. B [ask turtles( W0 N8 R) \4 m( T0 q
[ visions ]]# ?0 x/ v) p4 F7 i6 _! v( G; ^" ?- i) f
tick
# r, Z. a1 d: q6 y/ ?% H update-plots
3 h$ Q/ ~! Z$ `. wend
G! p Y. ^6 I9 _: g# xto visions
2 t L0 c3 _* _) q" [9 w set vision vision + 1 ; Y0 z+ [2 R4 m7 O* p d
end
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to turn-towards-grain , u+ X5 o& g0 b! d* m
set heading 0; p" c2 \ @, g# Y0 p
let best-direction 0( d: `2 M, b) A) K1 j' O Q6 i+ ~
let best-amount grain-ahead
P5 q: g5 {; U' H% q set heading 904 u0 [3 W$ y8 J0 Z; x
if (grain-ahead > best-amount)# J1 `" p7 _5 S; J% ~) B
[ set best-direction 90
8 G) Q/ k% M7 t3 r4 s8 o set best-amount grain-ahead ]. I9 s# f9 Y* {4 b
set heading 1807 n1 r- ?; l. |/ z, J
if (grain-ahead > best-amount)
# I4 I4 Q9 u G6 h8 A6 o ~ [ set best-direction 180
2 l% L. }: t" P set best-amount grain-ahead ]( K5 T, Q! B# [* x
set heading 270. {" j& n z- ~7 K1 W( Y/ A
if (grain-ahead > best-amount) W, S6 E7 d$ Q3 q" b. V
[ set best-direction 270
1 e8 D, j; A8 j5 B5 j set best-amount grain-ahead ]" y% C5 I- M& ~- {
set heading best-direction1 L9 d: c$ F- o. E* s0 B7 ^
end8 a; u- S" Z" g0 e7 l
4 `# Z- }0 Z& F( s R% y' t/ [
* s$ p( V+ c# w* _: x3 S4 eto-report grain-ahead
& p% W, W' z3 s% M8 s6 b' Z let total 01 c1 X0 }8 R, \! a1 Y% ^
let how-far 1' a- \9 }; e1 x. H7 F+ d0 X
repeat vision
$ P4 z6 K9 _: m! y9 { [ set total total + [grain-here] of patch-ahead how-far1 J( x7 n9 h5 p/ X; @! n/ E
set how-far how-far + 1 ]
Y2 v! { `" `' K1 i/ C) Q report total
; k3 ~7 a/ ]# [4 V- F7 mend
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to grow-grain 1 p! b. s A1 m+ ~# g* D
if (grain-here < max-grain-here)
. H- f1 ]6 Z: D [ set grain-here grain-here + num-grain-grown& @7 c4 X! f0 |1 `8 W9 {! M% d' O9 i
if (grain-here > max-grain-here) # e7 c9 C/ U0 r% c
[ set grain-here max-grain-here ]
. C- B |: n0 \ I$ d4 A recolor-patch ]
! J0 i3 r0 k" k9 y5 H6 h6 [end
. `6 o& J7 \( A9 ^to harvest' G/ u* L+ }3 X5 X0 C' k
ask turtles
+ i _- Z A. K; D, f8 l1 X8 O: D8 V N [ set wealth floor (wealth + (grain-here / (count turtles-here))) ]
1 J8 R- T, H, B. @" L ask turtles
. o1 w0 x& K( G) ^9 e [ set grain-here 0
6 Z5 M5 W9 \% Q) w# O' ?( ^, G& B recolor-patch ]
' I' K" y+ k } o! V* U6 X/ q" s v+ J& `
end
7 ^* C: _4 H/ I: S- ?( z
0 R3 q. a p5 y& wto move-eat-age-die 6 P) A5 S3 b0 N) A; c9 Q
fd 1
8 T4 q7 M# ]. `! W6 m) m+ { \ set wealth (wealth - metabolism)( U- |2 q6 ] j4 C6 G6 Q0 J8 m
set age (age + 1)3 Z5 r% W8 c' m- d
if (age >= life-expectancy), h9 w- S& [* R9 W
[ set-initial-turtle-vars-age ]
0 s/ g- j% E! F* { G0 Z; O. O if (wealth < 0)
( x# i' a! O+ A4 O, F! b [ set-initial-turtle-vars-wealth ]+ O5 W, l/ F6 P% k3 v' t: c
& o( H& T" N4 _1 Y- k7 M8 Kend5 \9 P0 Y/ z% G0 c( g6 @
% ]- E4 y! T( i4 t8 x0 J( J& r7 g' W# ?& w) z5 d" d1 e B: a
to setup-plots
5 P1 x) H6 i- w& u set-current-plot "Class Plot"
$ R" T$ |# h1 J8 o" E+ @3 Y$ L! Y8 [ set-plot-y-range 0 num-people
' x1 ]) B6 j' B8 | set-current-plot "Class Histogram", M. h1 y& y% q$ d
set-plot-y-range 0 num-people1 |) z( L4 I' I0 e
end
2 }! i: i1 Y) Y1 n8 ~0 K. G1 g3 ~5 T. q4 C; c% B' Z
to update-plots
3 r+ ~& a+ {4 P8 v \ update-class-plot' ]+ H, i- W( C% ^
update-class-histogram7 v5 x9 ~6 T; E7 ^( S
update-lorenz-and-gini-plots4 m3 ^* r& \1 Q9 O0 ?7 R+ ]
end
' B. \( N' O' d; U. `: e6 q2 j ]3 x3 y! ?9 g
to update-class-plot$ R; X- s/ I O2 s Z: x
set-current-plot "Class Plot"' z2 H [6 j5 K
set-current-plot-pen "low"
. z O. s6 V# J plot count turtles with [color = red]' W0 o, c5 G& c4 N: V
set-current-plot-pen "mid"" Z- \. x- [, U" S1 j
plot count turtles with [color = yellow]! S2 b; G3 |2 |, Z
set-current-plot-pen "up"% T M! ^+ h- d0 C$ w
plot count turtles with [color = green]
. e0 Y0 a9 v0 g Y! Yend
8 A7 O t' {$ k9 w; \. @; w4 U' q* J' X
to update-class-histogram& Z$ L4 W9 ?! t7 T7 |' x
set-current-plot "Class Histogram"1 }3 Y; u; E P0 m+ b& _
plot-pen-reset
9 {* C3 }4 U% b3 \8 g set-plot-pen-color red! K/ J( p6 c7 o5 g8 u
plot count turtles with [color = red]! b! c" `' T9 `8 f) Q7 H) w2 P
set-plot-pen-color yellow) X4 v1 `! S2 S" O8 x
plot count turtles with [color = yellow]
% F# C/ l0 ~; M* E' I; x( I) C4 f set-plot-pen-color green
- N: b" |, g D6 M6 c plot count turtles with [color = green]
# m+ b- i1 l7 R7 @+ jend
; ~; \7 d/ Q8 N4 d" ^to update-lorenz-and-gini-plots
) m, S2 r8 ?6 V0 R set-current-plot "Lorenz Curve"
+ \1 p. g! \+ G clear-plot( `; Q- k8 Y, n' F# G9 H. i
% j4 L! @' E: t. j& a1 j7 Y
set-current-plot-pen "equal"3 V9 n# N' p- v2 _" g+ B- m
plot 08 q$ S. _4 P+ G) K9 c
plot 100% H: r4 h! {/ R# j2 {
' [( G! J$ ?( L3 G' e
set-current-plot-pen "lorenz"; [. f: b. H( _7 C& I
set-plot-pen-interval 100 / num-people
& u# R2 {- m) x$ L plot 0: r6 B. Z4 x$ d0 h3 g T. d7 u7 F
/ z3 b$ B U! {) Q9 W let sorted-wealths sort [wealth] of turtles
) I. X- F: `6 e let total-wealth sum sorted-wealths, j& D- _% ?- Y h. j5 V3 |) t/ q7 d
let wealth-sum-so-far 0; [( x' U' ~( ^' K
let index 0
{ w! I e6 S0 C) T' {3 p+ B let gini-index-reserve 0
& f8 E; k# z* b9 l, H3 }# [' g% x- L0 D; _+ m
repeat num-people [
! S+ l: C4 J/ W a9 B set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)% Q( }7 L4 ~& } D
plot (wealth-sum-so-far / total-wealth) * 100# b- J# ]1 k$ B# z- I
set index (index + 1)
2 {, F" ]8 T; R4 ~2 l set gini-index-reserve" W7 u0 a* i2 |- b: m7 ^
gini-index-reserve +/ [- [+ Z( X& L W7 ~" r7 A" k
(index / num-people) -
$ u, j$ P: r. Q# E; o. U9 V (wealth-sum-so-far / total-wealth); d3 p% ? v, |$ ]! d# j
]
3 |0 N1 |1 \' c6 k# y T$ Y
/ o& q/ V+ c: p set-current-plot "Gini-Index v. Time"( T9 \$ {6 M- R
plot (gini-index-reserve / num-people) / area-of-equality-triangle! Y' d/ ~/ r# X/ H" }8 v. E
end
* p* s! Y9 ]- X6 K) Kto-report area-of-equality-triangle
1 { M- d. v* G1 c. L$ p3 j report (num-people * (num-people - 1) / 2) / (num-people ^ 2)
) l$ R. l, V: bend |