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
& e5 f: h! w! F% f6 }2 v9 {& {globals* `9 H5 N) ^1 @/ y6 Y! ^
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max-grain
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0 q, y7 S N& q7 L0 F+ ~patches-own4 \* L: A& u# c
[
5 ~' p3 r5 ^8 B' Y/ j2 g grain-here
6 x/ |) `, G( @; v' S" C max-grain-here
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6 h% y( g/ R3 ~/ D! ~* \* e, a6 X5 y- q) [7 \3 Y
turtles-own
+ O0 S; o( I c) s5 M2 o9 L[
) e, w) [# G% S. p age : ?! a2 F- p5 G% V
wealth
; R/ B9 \7 D3 Z life-expectancy
, @; u6 \* p; H6 y7 ]* t' ] metabolism
# z; R9 q4 Z+ }2 _7 a vision/ ^9 r9 z4 _% O; a
inherited + i% N1 y$ E. `
]
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+ S' k% i: D$ {( C8 h8 r A5 l9 P7 C; J7 l9 d
to setup
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% i7 x! h/ P! I+ o, ^9 d- ] set max-grain 50
! r5 B( @# i3 F6 s7 b* s7 K setup-patches+ d% P. v1 Z$ _, l
setup-turtles" K3 z6 }. V1 ^% ]- z- s
setup-plots- a0 M5 d# y+ ?& i+ N9 M4 t
update-plots
n8 S1 A4 g; Eend$ K* i; t; g6 L4 e: z- `8 I) f P
to setup-patches- S: ` d! d& m# @1 S
ask patches5 i3 n+ ?; _. o2 N; D4 n5 V$ u
[ set max-grain-here 0
0 X) ^2 S- a; z( z3 y, ^ if (random-float 100.0) <= percent-best-land
: B+ D' Q( q2 B" W& l1 { [ set max-grain-here max-grain
" t g4 D8 n% P! r- c2 J+ C3 e set grain-here max-grain-here ] ]
& ~9 F# p9 T+ i3 J5 a' C repeat 55 q* S9 V8 `& ~9 [2 a! ?
[ ask patches with [max-grain-here != 0]
5 m% Y& X# y; T, B& v+ k; q [ set grain-here max-grain-here ]
5 ~# E3 d, H! G diffuse grain-here 0.5 ]; l" v" p- _$ x4 L5 J) \
repeat 101 J/ C7 P, F+ P- T" c
[ diffuse grain-here 0.5] , j1 _1 V( F3 w. U- a) Q8 k
ask patches' H, [' E8 D9 P8 j" I
[ set grain-here floor grain-here 2 \) h. S. E4 Z# i( q# x5 h
set max-grain-here grain-here * g6 F7 e# c3 Q6 O0 q
recolor-patch ]: K0 V1 q, B' }+ _% `
end. D* I7 R6 o0 n% ^; H+ N
to recolor-patch
8 W5 H: @2 A8 K$ z/ W0 p* B/ C set pcolor scale-color sky grain-here 0 max-grain
. X. ?# h6 J( ?; nend/ z5 `; m1 T) y4 J3 V
to setup-turtles- g0 T8 ?; ?3 t7 f
set-default-shape turtles "person"
1 d2 A1 I) p' s+ g' @ crt num-people5 Y( i. K- Q, K( Z3 A
[ move-to one-of patches 3 ^5 X9 u! k. O3 f# g" i
set size 1.5
6 C9 I ~/ B3 h* E* I set-initial-turtle-vars-age+ i& O' f5 W: g; _+ Z$ G1 G3 R0 w; e
set-initial-turtle-vars-wealth. [, P' I) H4 f/ p" T
set age random life-expectancy ]
0 _: a. R1 F. A6 F/ n recolor-turtles
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to set-initial-turtle-vars-age
9 i: z, Y' n" f& o, ^$ ?$ c let max-wealth max [wealth] of turtles1 o6 p% w; Y ~! ]* q% G# u6 n
" F5 Z3 k1 \: _& |$ u ifelse (wealth <= max-wealth / 3)/ e1 Z; Z6 h( A% Z
[ set color red " v9 g. b( u: Y8 N8 u+ V& _1 n
set age 0
5 o) }- Z P0 m; U% P% ~. b# L: ^ face one-of neighbors4 9 [' s% P `( g5 C2 y8 J9 {
set life-expectancy life-expectancy-min +
8 z- o4 U7 x) V8 M random life-expectancy-max ) V: B2 ~3 \' ^8 g# \0 W2 p
set metabolism random 1 + metabolism-low+ \2 r6 _7 y6 v& H) O: @0 c
set wealth metabolism + random 30
}" g$ r& P1 |1 _+ G' j set vision 1 + random max-vision3 |6 C+ |% u* b6 a. T+ Q
set wealth wealth + Wealth-inherited-low ]1 H8 }- n% f9 ~) s2 E; z: {
[ ifelse (wealth <= (max-wealth * 2 / 3))$ w4 ]! w, {: b' p; l
[ set color yellow : Q9 D/ C- s: |3 s1 }1 ~: ]4 @
set age 0
: P( q1 @* ]; { face one-of neighbors4
$ S& ~* q; M" e set life-expectancy life-expectancy-min +
3 }# a' J* Z0 c% L random life-expectancy-max + 1% x4 n: r) G) u' z) d
set metabolism 1 + random metabolism-mid
7 [' u; o3 W* b3 r9 R" {; P set wealth metabolism + random 30
$ |* {' y3 ^: L set vision 3 + random max-vision
7 B& s/ y1 U G0 i6 j4 n set wealth wealth + Wealth-inherited-mid]* o) p: N% B' n
[ set color green
1 Z B4 `: {. J" F! n- b* Q- [ set age 0( f0 m, Z: L: `* Z3 v2 E& V
face one-of neighbors4
* k2 e2 \! M3 s set life-expectancy life-expectancy-min +, B$ M1 ^! U9 ]. c4 N
random life-expectancy-max + 22 x2 N3 A8 E: v
set metabolism 2 + random metabolism-up
; p0 D: V! }5 T2 O1 K9 @* n* A, R set wealth metabolism + random 30. X% C3 b5 \: ], `7 M; F" g, }
set vision 3 + random max-vision
/ I0 ]9 }. i2 Q) y. V) k set wealth wealth + Wealth-inherited-up ] ] . E; ~' B* R- P, I$ e8 `, I/ r c2 I
2 a) C- L. \2 t* |end. C4 g% L) a. \( l. O& G
to set-initial-turtle-vars-wealth* d* [. ~- }0 H3 k" m1 \
let max-wealth max [wealth] of turtles) P, s3 M- `# ]8 [
set age 07 `6 Q2 U+ L, k4 `* {* D: ]
face one-of neighbors4 / o: x/ A1 W; `9 a
set life-expectancy life-expectancy-min +! u0 ]: ~9 L% v" R3 N- e9 R
random life-expectancy-max
& I8 F" W6 W! I) W: ^& P9 J2 e2 d set metabolism 1 + random metabolism-up
; ]/ l0 _( q) T set wealth metabolism + random 30
2 r! v2 y* ` H3 ~# v7 W set vision 1 + random max-vision 3 ~ f- T; r+ r: h! X1 W5 h
end5 ]5 E+ b1 f/ z i! G# `/ m9 h
to redistribution
7 t8 A( V) c3 \# Qlet max-wealth max [wealth] of turtles
5 L$ p% R& r: k( j5 R( D/ {2 @let min-wealth min [wealth] of turtles. M& q2 f) s4 b$ I
if (wealth <= max-wealth / 3)- }- A5 u5 U7 f* s3 ?' T8 ~
[set wealth wealth + Low-income-protection ]1 L$ J& s$ q! F# K! S. k' X
end2 Y/ }: ~% e% F$ P; |. m
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to recolor-turtles; A# [) E( A5 o4 @( m
let max-wealth max [wealth] of turtles
/ t4 h/ e, f4 J/ ?6 p1 X& V ask turtles
! i& N( I# U) p2 _8 o. ` [ ifelse (wealth <= max-wealth / 3)0 Z- r1 k- Q: l
[ set color red ]
" Y7 p5 d8 p X0 O- ]) v [ ifelse (wealth <= (max-wealth * 2 / 3))* ^) L( o4 d6 K! R6 P
[ set color yellow ]' [7 _, d5 n; j/ N" J% J
[ set color green ] ] ]: { D7 ]' P( o, ?$ P$ D
ask turtles [ifelse show-wealth?% V6 k k! p% L" F5 v5 F$ d* k8 w
[ set label wealth ], u& r% d5 e) S. c/ l
[ set label "" ]]
2 m) T0 i( A: S8 {end
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: R- A) K1 @+ N4 k3 Y( Zto go) A2 K7 t' i& {, z5 [6 [
ask turtles; j8 l U% G. E) A& Q; V
[ turn-towards-grain ] 4 g0 U& ], E) x: e$ C* q2 `
harvest
3 E- n" g9 n0 v+ t; n) O' _( j ask turtles/ b2 X5 p# q: Q' E' K0 x- {5 F9 k
[ move-eat-age-die ]
1 n8 }# z5 |6 P3 m recolor-turtles. S/ {. v( n! I2 P: T% v% `5 b, h
if ticks mod grain-growth-interval = 0
. [3 Q* X1 F! w, D9 V! ^! W4 U [ ask patches [ grow-grain ] ]0 }! ~6 d2 M# w/ E# G* q
5 k& U$ g" m& V/ [) k1 U
if ticks mod 11 = 0
( m5 n9 w1 g8 I) d# F" }% i4 o [ask turtles
; J- ?9 Y3 I* F! a. O' @8 s [ redistribution ]]
/ o0 U) I1 G4 S( ^ if ticks mod 5 = 05 l V" P0 u; q4 p+ X+ _) n+ g
[ask turtles( B7 t; K. C2 J; S" @
[ visions ]]5 h2 Z3 O# j8 R2 U4 J8 t' F
tick
. H: i1 k8 O3 R update-plots
: i' r0 _' ^" g0 D8 g6 M/ `end
' W9 Q! e! X+ V- X2 ^to visions
. U# l0 [& }) r6 _ set vision vision + 1 ! n$ E$ @5 m! w% ~$ ?7 f+ Z
end. [( a% s$ z" l& Q% C( |
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1 z& Y& r- d4 K, lto turn-towards-grain
0 F& p: T5 Q" v" J$ O5 t& U' @ set heading 0
& a1 _# N6 L! V let best-direction 0
7 r+ p, p7 X$ `" P let best-amount grain-ahead
n4 G* u) \2 n0 {, p. W- q set heading 90
|3 y9 w |5 n6 X. u if (grain-ahead > best-amount)
: ]2 s# O. b8 y+ ^# ]1 C [ set best-direction 90. L3 c0 O, c1 f
set best-amount grain-ahead ]& u4 q& W3 c3 l
set heading 180! |) q6 Y( V+ l
if (grain-ahead > best-amount)$ K6 {/ _& z5 E% O2 H/ h
[ set best-direction 180+ t6 ?4 f \! J# l6 f
set best-amount grain-ahead ]7 W5 i! b% B( u. v3 c
set heading 270
& r5 V1 w+ _" N5 V! E4 x if (grain-ahead > best-amount)
& Q4 _6 x& S3 L, c [ set best-direction 270
2 w2 q- Q7 ]3 n* z set best-amount grain-ahead ]
( |; C7 Y! ^2 ]* C" s set heading best-direction
1 b/ M0 Z2 M8 G4 h5 H! q( Gend: k+ ]1 l5 c8 k3 P+ `- F8 o9 w1 e
2 |5 q+ _) t; h! m. C: |2 L2 N
2 T/ [+ q1 B# c- Y- H2 L: ]to-report grain-ahead
2 T# j4 T% l* b' T let total 05 v! {0 Z* h* }" Z
let how-far 1; M' n/ `3 j3 G$ b% L
repeat vision' ]2 X% I8 f7 G& M) l2 n
[ set total total + [grain-here] of patch-ahead how-far
0 @$ e- c; b5 v$ f3 S2 {! f$ } set how-far how-far + 1 ]6 L; X. X9 ?" k+ Y5 M$ N
report total" q3 o( R* ^+ [# y2 G' I
end
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to grow-grain
( m% x8 N# _3 w if (grain-here < max-grain-here)
$ O+ ]0 G( h9 A& m. Q [ set grain-here grain-here + num-grain-grown3 y6 J4 a4 g/ x' Z5 D) @
if (grain-here > max-grain-here)
' ~8 [4 j, @, c* e; f [ set grain-here max-grain-here ]# @' V5 a6 H' y" N
recolor-patch ]
9 J# g% E$ L$ y$ I# L% j( Mend" @# O: h- ?6 s' ~
to harvest
# V& @$ P0 @. R4 ]# n6 s( o- w) ~ ask turtles- `, g+ W7 V5 D
[ set wealth floor (wealth + (grain-here / (count turtles-here))) ]( K4 l8 R7 y7 O1 q2 H/ z
ask turtles
) l! J6 s, f. q9 U5 L [ set grain-here 0
, P* w3 O+ F3 M* s recolor-patch ]8 y1 v# C* o# ?& ~- P' J# I3 W
2 e9 B( |) \6 U/ p
end
% k6 R+ f2 Q7 e8 d8 S) V
' {0 O0 ~+ ?4 X$ {to move-eat-age-die ' j* |5 @" ^0 ^( y
fd 1
6 P# p! [# x; h- M/ b set wealth (wealth - metabolism): k+ `0 w+ u) S1 W8 }
set age (age + 1); }3 u) O( k1 P
if (age >= life-expectancy)4 t; t! Z8 V2 X9 y, ?
[ set-initial-turtle-vars-age ]. M& z0 z2 o( a4 Q6 H$ S
if (wealth < 0)7 X( I* h+ w9 m3 v
[ set-initial-turtle-vars-wealth ]# D! A( h1 X/ N8 F
2 f/ C" I7 W d
end
4 T- ^( P) O! f" I7 e0 Y3 i4 o
7 R8 R) x' j$ o' @) Y" a- P( c, v& I9 `
to setup-plots+ N) l- l" N# C: E }
set-current-plot "Class Plot"
9 k( Z' Q; V! ^' N9 U; K' l set-plot-y-range 0 num-people$ G9 i1 n9 @" V9 b) H
set-current-plot "Class Histogram"* l4 b5 G7 [1 v. A& L
set-plot-y-range 0 num-people
5 @* ~/ J+ K K1 j% ]# W% tend# j: R5 }- W6 ]3 r6 e& j0 F: Y0 _" W6 f
$ o# t7 Y/ L- V1 u- p6 c3 u# q% w
to update-plots1 ~4 r0 V/ _' X% ?* ?3 w
update-class-plot' K# F" g0 {/ N
update-class-histogram
6 A/ A; F: \. Q/ |5 _, {* b$ n; U$ m update-lorenz-and-gini-plots
' |# D- [4 [: L; {5 W6 i6 xend
, ^# ^" j4 I4 m% G: Z8 ^5 o: q* {$ a. c& O1 F7 ~
to update-class-plot2 V2 y6 P6 A3 v2 k: T+ C
set-current-plot "Class Plot"
) `8 t5 O# l2 Z( h# _/ z! T set-current-plot-pen "low"8 U3 Y- c8 m( E! a4 c2 ]
plot count turtles with [color = red]
+ f N3 I& D$ C# ?- `8 g# o! q3 p2 @ set-current-plot-pen "mid"# V# e9 l) V6 j- K
plot count turtles with [color = yellow]' o# g; N" U% ^5 v# l6 t5 o
set-current-plot-pen "up"
) [ i& ~6 _+ i7 G plot count turtles with [color = green]
7 g# y9 |2 f! m" qend
: R! I9 d1 P+ @: L3 l. \% @
( z" f F" j! [) G1 ~( Nto update-class-histogram
+ \9 j: {6 e3 ~8 F* U& l/ j# h" V& M0 v set-current-plot "Class Histogram"
2 J: Q- H/ A4 K9 y- Y* ]. `5 C' Q plot-pen-reset6 o5 }- q# G9 c- u+ l/ v: S' l
set-plot-pen-color red
: n# ~! h1 p) l& Y P8 K- d# T& d plot count turtles with [color = red]
u# ~( w3 i! u( w set-plot-pen-color yellow
# v- X" V; h0 c0 J8 p! B: Q plot count turtles with [color = yellow]- |0 ]; C" d. n# Z: X
set-plot-pen-color green
9 o% c+ u6 ~: B6 S1 @4 N0 _! ^* q plot count turtles with [color = green]
# `$ J: ~/ n4 Vend5 q- C) Z1 `. A! a2 _
to update-lorenz-and-gini-plots
/ z! D% |$ L! a4 _! l4 u" }& S set-current-plot "Lorenz Curve"
# F+ y* g/ y- u9 H clear-plot
" `$ ^* v X2 B$ K7 ?
3 o; M- |' n! n4 h: U" R) t2 i set-current-plot-pen "equal"
5 T/ }6 A R; n+ h/ n plot 0
& x Z9 j6 ^: b1 P; H; W) l plot 100
" l6 t6 f; R/ S; k* D7 Y+ H
9 J2 a4 u2 \; d% o5 U, t M* Z set-current-plot-pen "lorenz"
1 U& U& n U; e, U. T* `6 | set-plot-pen-interval 100 / num-people
4 o1 O" g% U& z7 ~0 c- W plot 0) ?1 E5 S3 R, V% h0 u& N8 a
- V3 u- s5 |; J& ~
let sorted-wealths sort [wealth] of turtles- Z7 V- A) A8 R( l* T2 x; T c
let total-wealth sum sorted-wealths
( h7 K; E8 Y, H1 X6 m, H& E0 G6 [ let wealth-sum-so-far 0
& o! z8 L" e2 N/ a! _ let index 03 Q M1 n4 [3 ?/ r
let gini-index-reserve 0
: m1 e8 g) ~' t. G4 [( r
6 K: K( ]8 M3 B4 Z repeat num-people [
) N6 Z7 u1 }$ a% i set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)
# G' E {# S% z1 T6 ?$ G D2 B7 k plot (wealth-sum-so-far / total-wealth) * 100
7 u$ N7 O$ X: q, B8 k& [ set index (index + 1)% x8 z; y; A/ O; F7 N% z
set gini-index-reserve, B9 m/ M2 G% i: A
gini-index-reserve +
9 c$ A0 z6 r2 a$ f; L) E2 h (index / num-people) -3 v, f0 y* j+ J( B4 O
(wealth-sum-so-far / total-wealth)6 m, y0 \1 j# S1 E/ t% y: J# w! q
]0 o) S( e _: p5 Z
: g/ c- k5 N/ b3 m set-current-plot "Gini-Index v. Time"
- H3 L- Y( F. `0 P" ^' ]. A plot (gini-index-reserve / num-people) / area-of-equality-triangle$ N2 Y6 @9 W# U+ j, d8 J0 w5 @2 V
end
% X+ T# L: ^' zto-report area-of-equality-triangle
7 _$ z, w. _. c) { report (num-people * (num-people - 1) / 2) / (num-people ^ 2)
8 s9 x: z _3 w- I! tend |