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. k9 v& v( j9 ^6 j
globals
4 P/ p# f. c( f' O: m9 o& i[$ O9 J8 J# O" O
max-grain
. N6 b/ F4 q x7 m% q. `( E4 u8 A' M6 ^0 i8 `' U
]1 W& A5 p' }: \0 \
" a0 b Z5 V& q0 epatches-own
* M4 {8 K4 o2 B4 ^3 s[! `7 w7 p# u3 v2 I/ W+ @# O
grain-here
7 V& m: V! `1 x3 i max-grain-here ' }: G6 y0 E2 g g ~
]
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turtles-own m6 y+ H& o. f% d# R* L. @. t5 I- Y: |
[7 n4 q5 }3 {% O" _; o% R
age
* K0 @. P, X$ n* P$ d wealth 1 H8 }+ j) H$ L, B$ C
life-expectancy 9 x E2 g5 O! `5 B; S7 k
metabolism 0 @2 U" s5 ?! e c! I: z
vision
1 l, U* b6 i, |4 r7 Y9 k6 G P inherited
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2 }' P$ l5 S: a) A& a8 h1 o& c) A% k; E4 T6 O& y
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to setup( r0 r. C: c/ W% v6 j6 w" W7 j* A
ca
5 a. p% @7 k. T- G1 N set max-grain 50
/ M, ^! U; W9 `3 {/ X, S: j setup-patches% E6 j+ R/ `+ @
setup-turtles# I5 z5 N0 ^, x9 z# F3 W2 ~" u2 Q
setup-plots
) o2 j/ X9 |& \) @ update-plots1 c- ~; p: Y2 f" [. y
end3 n8 b& }# z1 a2 s; g8 ?, f
to setup-patches
' ^+ ~' @5 L5 C6 y5 t* [! K% ?3 [ ask patches
2 S3 }7 r( B* t, { [ set max-grain-here 0& U2 O, E- @; B, V9 U
if (random-float 100.0) <= percent-best-land
1 m, ?# _ e% B, u; e H+ o, N [ set max-grain-here max-grain) q" j! R* |5 k7 S3 x* A; A
set grain-here max-grain-here ] ]
* w, | a$ X( v: @ repeat 5
( P' C, E# F4 e( y& B i [ ask patches with [max-grain-here != 0]
`1 c( U9 C. G: g! I* V' K* W [ set grain-here max-grain-here ]
4 j. d! |" I; `1 Z6 O1 ~* W0 p+ v diffuse grain-here 0.5 ]
2 ~, L7 g4 H3 g+ x' O$ c repeat 107 @( Z" u- @3 c n i
[ diffuse grain-here 0.5]
$ P; D% G( U3 t- D6 e0 M% F ask patches) Q1 z* R. @! B, H- e5 P" c2 b5 G
[ set grain-here floor grain-here
4 r3 z! J1 z |- g set max-grain-here grain-here
" J! H; s2 H8 I7 }* T4 H' ?. L4 z recolor-patch ]
. s1 L! x5 F& Rend W- T; b: l- R
to recolor-patch
1 M+ _0 ]' j) e+ A set pcolor scale-color sky grain-here 0 max-grain' [7 P8 p2 O/ P- _5 I g
end
# j* A; C8 K! N& k7 Z8 j0 x9 `0 \' Yto setup-turtles; I1 h3 u G* k5 {1 Y
set-default-shape turtles "person"
3 S( m3 C8 T: E+ f1 _, l crt num-people# t3 v& J" n5 c$ i+ [8 T
[ move-to one-of patches 8 P+ h8 g. ?- I1 a) _
set size 1.5
+ ^+ Q. C4 X0 V set-initial-turtle-vars-age
8 A( s1 A5 v( e6 J$ Z" z+ v# } set-initial-turtle-vars-wealth% _ e+ F4 f% ?8 ]0 _
set age random life-expectancy ]: T0 o% a3 C# l& Z$ j
recolor-turtles/ I) _ W/ ` v4 k( d
end2 e1 h/ ]) A c' p
# n8 i6 ?7 }6 w; y; [4 yto set-initial-turtle-vars-age
! L3 h3 Z2 X0 V let max-wealth max [wealth] of turtles
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ifelse (wealth <= max-wealth / 3)- v; [( _/ v& ?8 S- Q
[ set color red 0 L3 S: O0 f/ ]% S% ^
set age 0
) F, c6 a! w5 x+ ]) o' B9 r2 N face one-of neighbors4 2 _4 n9 a* {* J, L! P& Z, d6 N
set life-expectancy life-expectancy-min +4 O! O, A7 t1 X* Z5 Y
random life-expectancy-max / b& d& W1 I/ F9 U J7 Z5 N
set metabolism random 1 + metabolism-low
7 V" A& ~& @; K2 | set wealth metabolism + random 30
( C3 m. h& f* C' v6 H/ } set vision 1 + random max-vision2 Q) C; a( `" Y* a* Y, T
set wealth wealth + Wealth-inherited-low ]
' d9 Z8 w5 b U3 w/ U' x! Y( @4 ~ [ ifelse (wealth <= (max-wealth * 2 / 3))
% y( [- s' E' v0 Y! M3 L) |& c. ? [ set color yellow : @0 c5 `" x: y. y; Z
set age 0
- Y, ^$ N! M( C; x3 {3 y$ ? face one-of neighbors4
9 I" t+ q9 |" C# _ set life-expectancy life-expectancy-min +$ ?: m, z8 j8 N }0 T& K0 w
random life-expectancy-max + 1" g2 M0 K n: n/ S4 f$ f
set metabolism 1 + random metabolism-mid
( F; r n: x, l5 e set wealth metabolism + random 30& l5 S( N& k0 J. l* o; {* M6 b* v
set vision 3 + random max-vision
! z$ F. p' W& l. I; r* U) H8 Y set wealth wealth + Wealth-inherited-mid], R/ Q% m- e2 J5 ]+ f% g2 ]4 \1 _
[ set color green
7 o! Q3 r* `. \; F set age 0" |+ k8 e; L0 M2 P" q
face one-of neighbors4
% b/ `& \ C! W set life-expectancy life-expectancy-min +# M$ d8 e$ E- L6 l1 H
random life-expectancy-max + 2
- l5 B- @% @3 t0 w set metabolism 2 + random metabolism-up
! g2 X- ^( m8 I& @' V7 } set wealth metabolism + random 30/ T- k* n( o& r: b/ F
set vision 3 + random max-vision
6 h3 S* S* U6 t, O0 a R set wealth wealth + Wealth-inherited-up ] ] , b" K" p/ ~) U* k% u
3 o: H1 {; W5 p% ~, ^! u( Zend- K" H$ H- ^ F7 W" j2 _) [
to set-initial-turtle-vars-wealth% |: Y" L2 G1 o# f1 E; f
let max-wealth max [wealth] of turtles# s( E1 |% a7 Y
set age 0# Y0 X! o- M, d. j
face one-of neighbors4 3 N, B' B: P$ q# T {9 W7 {
set life-expectancy life-expectancy-min +& G% Q" s$ f* \! c: E% y
random life-expectancy-max ; a' y! o9 {5 a1 u
set metabolism 1 + random metabolism-up: _; ]8 K6 M2 C* B
set wealth metabolism + random 30% W5 X- u4 E; S0 t3 c
set vision 1 + random max-vision 9 S+ D; M& I. i1 B+ J
end
+ V6 K4 R! O oto redistribution; u, z; @" |: W% D0 s
let max-wealth max [wealth] of turtles. Z* l3 D/ K, w& B' i* \+ C
let min-wealth min [wealth] of turtles
+ w# n9 I- ]) b7 p3 R% Qif (wealth <= max-wealth / 3)
) O, g+ r/ C5 y* z1 U- x# H [set wealth wealth + Low-income-protection ]* e% M- [% ~9 p- F& y) \5 j
end
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to recolor-turtles% e8 b- S% [5 I8 k, H6 ^; I
let max-wealth max [wealth] of turtles3 a* z: j6 @2 f# s, Z- y- s8 Y
ask turtles
4 ^& K! p P1 H2 n0 V [ ifelse (wealth <= max-wealth / 3)% U1 e7 B4 R0 i; y/ e- [. Y: U: V
[ set color red ]( Y0 @. P0 r: o0 p/ i% E
[ ifelse (wealth <= (max-wealth * 2 / 3))/ J- n1 O3 @- l( h. n
[ set color yellow ]" C. z% L- H0 c% c: v5 v
[ set color green ] ] ]* o2 v; b2 ^! j u
ask turtles [ifelse show-wealth?
! j( t% Z4 a `/ B/ G5 z [ set label wealth ]/ m- [+ |5 h9 X
[ set label "" ]]" L4 Z. N5 g2 e9 | `- E
end
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k# [0 P/ o, [ d( J ?$ ^to go$ H% U9 ?/ c" Q8 ~& r, {- E `
ask turtles+ @8 X, _9 D4 H) c2 c
[ turn-towards-grain ] % D. `0 m; i" `) R
harvest0 l, m8 Z+ A& Q* z6 c0 d2 z2 P% W
ask turtles% L- G" e0 p j# z
[ move-eat-age-die ]. O) r% m( C1 A% K* _
recolor-turtles( b4 g/ j! _. ]/ f7 Y( a+ ~4 D
if ticks mod grain-growth-interval = 0
. p, K! e2 E- U6 `$ F$ \ [ ask patches [ grow-grain ] ]* K7 d4 ]; C* K; s. Y a8 Z
/ E7 D1 R. d9 R9 q4 U2 X3 z/ Z! Z, b if ticks mod 11 = 0
, i2 u( S2 t a$ J8 f% u- H+ m [ask turtles* X" I! y% |% Y
[ redistribution ]]
9 l( x( R3 P$ q1 s& q, i, x if ticks mod 5 = 0* ^) C: \0 _+ `- Z! N3 B
[ask turtles
/ Q4 {& Y2 P, V6 U) n% u; ]' F/ o [ visions ]]* T G U5 Z9 b: M7 G5 z
tick
2 j, k0 C8 p6 H6 z+ s) d9 @ update-plots
' D9 j0 S+ K5 M O0 Send
1 g( ?: W( z7 l1 eto visions
3 o( }% _0 C1 b- a+ |, z A( I* n set vision vision + 1
' }# t. n7 I" y: e2 B! E! Uend
' n" ^+ f. h4 \) T1 @; i% H- j3 f8 y5 _! F- R! A
j5 r% X" C* C! d8 f, [0 ~
" R# b9 ^' l# S( `* \8 m5 H4 |+ A5 i; Kto turn-towards-grain
$ o K$ }5 c' _2 Y; J8 E8 k: ` set heading 0/ u+ T& C! g* R- u
let best-direction 0! }; G! w7 y: X. v3 f# ~4 L
let best-amount grain-ahead( }: k# }9 q5 I% ^# f& k
set heading 90" w9 O. O, Z$ j
if (grain-ahead > best-amount)5 q1 Z; _( w4 C) w7 m7 j
[ set best-direction 90# l4 u9 a( T. a* C6 i/ F- q( ]: ]
set best-amount grain-ahead ]5 s$ s/ ^, \6 u8 r' x& U8 s
set heading 180
% y1 e% {4 `% B/ i' r3 j if (grain-ahead > best-amount), r! W' Y) u& Y9 D& i9 P
[ set best-direction 180: p/ H }- V- O) U
set best-amount grain-ahead ]" Q& B+ h( L% E2 e' U: Y
set heading 270: ~! B+ D3 L) s0 U0 o8 k
if (grain-ahead > best-amount)% W* k! q5 g' ]# e. W' @
[ set best-direction 270
: g+ S% \/ P) u" W# A set best-amount grain-ahead ]
' `- ]$ u$ B# F( w set heading best-direction
4 {) k& [2 t* t. u- n+ B4 jend' K: {* n- N$ ]& \9 G
/ z) I. i3 a) w5 b. C7 U6 e9 ~5 {: t7 V
to-report grain-ahead
8 p7 o, h* ~* B. G) B; o, p& k let total 0
5 A5 C2 @3 e( y5 w! j1 p6 J let how-far 1
, h) o; w, v( D5 k3 j0 d; H4 N repeat vision
* P# c' z4 G5 {4 d+ r- |' p [ set total total + [grain-here] of patch-ahead how-far, q S3 g2 p$ J
set how-far how-far + 1 ], G; X: V$ L2 q. Y1 Z
report total4 X) |' S! C& u+ m7 E- {
end
9 D) {3 h. N+ t& n! M. u& \! L' ?0 \) j
* C) d/ x/ U2 D9 t: [to grow-grain $ k5 p# l- v; b }3 x* W
if (grain-here < max-grain-here), T% \* m4 c8 h+ E0 d
[ set grain-here grain-here + num-grain-grown
. n4 ?8 t) J3 ^% a1 T# N, r if (grain-here > max-grain-here)
4 _- j/ U ?2 S8 J+ M" D# V [ set grain-here max-grain-here ]. y! }9 L6 \+ H4 e
recolor-patch ]
+ ^ b: D2 @$ m2 Uend
$ _7 z4 l: w) w* W! _to harvest
& J: o# p# O: b ask turtles
2 i2 n7 X( ?, l: i' r8 z+ j [ set wealth floor (wealth + (grain-here / (count turtles-here))) ]
0 W0 y' ^# [# V1 A3 Y ask turtles/ A; ]& B* N! f6 u9 V, Z/ t7 i
[ set grain-here 0
8 N! I& U2 V0 g recolor-patch ]6 l: } m J) F1 f: Q
; U; ?5 j2 u# P6 @end% J% B$ O" j3 d$ H: a0 {
! r- U9 A0 h$ n
to move-eat-age-die
7 c% r. `3 Z6 u" Y( P3 I+ Z5 Y- D9 w fd 1
5 ?; w7 i1 `3 Z" E7 g set wealth (wealth - metabolism)
9 r8 {3 s9 \" u# z& A set age (age + 1)
/ ~3 L& J3 ~* Q if (age >= life-expectancy)
$ Q0 R, W! [1 s5 u* d. Q! s [ set-initial-turtle-vars-age ]$ v# r3 _! T& b: H1 k+ k4 N
if (wealth < 0)
# q1 F- B8 v; |8 @. n. g/ x3 @) D0 r [ set-initial-turtle-vars-wealth ]
- m2 m2 d8 Y: G' J! x0 ]# T- }
' Z |. q# c. p9 a2 |% ~end3 P8 q6 d, c$ f# W& f9 L
$ j! J& r9 s; B! h. A8 V9 N
( \2 R4 @9 X, vto setup-plots
& R* R4 H, s: Y& |8 t8 Y' V$ W8 h set-current-plot "Class Plot": L6 g& W" V3 ^3 N
set-plot-y-range 0 num-people5 O0 ^* H8 S0 K
set-current-plot "Class Histogram"% d6 G5 d& W9 r. f1 T
set-plot-y-range 0 num-people2 i( o2 h. {. _
end
+ ?. F; t7 {2 r0 ^+ g
: F5 g# s! x/ s! f6 Fto update-plots
& {6 X4 m! W, N# I. `( ~ M update-class-plot
/ C8 e, U/ F. Z+ K, A update-class-histogram' |3 g# [# R D; {! h
update-lorenz-and-gini-plots6 \; i* @7 P m- \# [
end
" M) Y8 d# {+ s6 o# u5 L' n/ W& N4 V* d3 i8 E# s' n0 j
to update-class-plot* T, M6 M4 @2 u7 E- ^% i1 Y
set-current-plot "Class Plot". O1 t/ B1 p4 d4 T
set-current-plot-pen "low"
3 D4 L# W# U, K! |9 ? plot count turtles with [color = red]8 Y/ p9 B; R6 Q& e7 b
set-current-plot-pen "mid"/ `# P# D( y. H: H, y7 J
plot count turtles with [color = yellow]
4 e+ H( L- p u set-current-plot-pen "up"
2 D% ]: x% q5 K! Y' I9 A+ ] plot count turtles with [color = green]' |1 X/ Y2 _4 F6 V( g
end
2 d; C+ \, q5 w0 v
! ~0 T2 U& [8 Q4 qto update-class-histogram/ w* g/ o/ c5 J8 ~3 ]6 B) e
set-current-plot "Class Histogram"* B5 [3 r- d- S4 r' ~1 Z5 M
plot-pen-reset* E" p3 s, ]" N: I% O" _
set-plot-pen-color red
- d+ D/ u- Y, E8 f$ g- ^1 q- c plot count turtles with [color = red]- P6 K$ {1 G$ J4 r
set-plot-pen-color yellow
- J$ I% o4 O# i. H$ ?8 `1 A8 w plot count turtles with [color = yellow]
+ V' o7 Z( }* o* T set-plot-pen-color green
7 j. o0 l6 [5 H, z* q plot count turtles with [color = green]8 y9 V+ ]0 \( p4 T( Y; d! W
end8 {' d1 r" f# A. u* l# E6 i
to update-lorenz-and-gini-plots
, f, l- V l! G$ F" i* u- Z$ v set-current-plot "Lorenz Curve"; E- ?" V* d7 Y+ K/ [6 E* M$ C
clear-plot9 Z/ O* J! p$ Z' I% F5 a" l
' m3 |- M' T, v" S
set-current-plot-pen "equal"
0 _; M: R3 x: z! } plot 09 z( O9 b, \& {1 A8 U; M
plot 100) E/ D: ]6 X5 e: ~/ |2 V j
6 k; o# B' R2 H. R7 F; u# [4 A
set-current-plot-pen "lorenz") a8 Y' F2 ?/ V8 q- v! Q6 ^. ]
set-plot-pen-interval 100 / num-people8 G3 |+ O) U- P! F4 Y
plot 0
6 `: u* i3 B/ @! {# ~+ Q; [
0 M: i' A$ [; X let sorted-wealths sort [wealth] of turtles# [, R4 |; U5 d9 Z% u7 V
let total-wealth sum sorted-wealths
& E2 c4 ^* z- ?( p* G# P let wealth-sum-so-far 0
/ h8 S0 r9 }2 |) }2 Z1 I) N! R% [ let index 0" K/ ~( V; W, _% p3 F" i* ^* g- j
let gini-index-reserve 0
, O. v& Q3 ^" t3 m
4 e! ^$ ?1 Q4 j/ g" n repeat num-people [7 v- s' c; h; h8 D& J8 h" L
set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)+ p, q% l4 d9 g) p7 w4 ~5 Y$ L0 g
plot (wealth-sum-so-far / total-wealth) * 100
5 q/ L+ e" c# a+ \ set index (index + 1)0 I( k' X- _6 _' O# b' A2 B: j
set gini-index-reserve
. C5 e$ s4 M. z7 q+ f9 z6 K gini-index-reserve +. P( a+ m. g% F4 |7 t8 K
(index / num-people) -1 ` Y0 I& E- | s- K+ @* b5 D
(wealth-sum-so-far / total-wealth)
1 U/ [- I5 ~' j ]
& V) Y9 N! c4 `$ T* K$ c5 W% }5 V5 i! c# H
set-current-plot "Gini-Index v. Time"
/ D% q) Y. s( @8 Z2 \ plot (gini-index-reserve / num-people) / area-of-equality-triangle
2 B4 r5 C! Z5 rend8 Z8 O, f% a% K6 j! W d% G
to-report area-of-equality-triangle
3 P7 D9 n0 j9 b& J report (num-people * (num-people - 1) / 2) / (num-people ^ 2)
# r$ i0 ~2 G6 d1 E7 Wend |