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$ h) p, x% q8 T3 e8 B3 B
globals& X: u0 Y& p2 @
[! f# O" t, q- h& Z) o. I
max-grain
0 t1 v4 ^- r, u: X$ H4 a9 X. D( b7 b5 m1 z5 z" b0 s( p
]$ k+ @; M( b7 M. u4 @/ ]% a7 z
: j. f+ S% [# g, o) z& dpatches-own
5 V- h! D# u2 H7 j1 E! C[4 h* ^! W/ }2 L9 s1 p# R
grain-here " I. h+ ?4 J; d6 i
max-grain-here
* x" I6 T, U! I% {]
( B! c# _) t& O' Q0 b" E" a0 ~( G
turtles-own" m8 m* [- N/ i7 l1 k, j
[$ k4 i- g. K6 B* _# s
age ! y) j3 A2 r+ a
wealth
. b+ h4 [: |* j! d Z* V% D( j% W life-expectancy ) q, K$ ?1 z+ V2 _5 k6 S; u
metabolism
, }/ m, q* C4 ^- w' I5 B vision; ^5 }2 J* }9 q3 ~9 L ?
inherited
. W# |. |" Q. T% [) Q: W R]4 j2 Q; T( ] d
9 K I, a. v" I8 V
# T" ?& e9 K' R& k2 b" {
to setup
/ N6 m0 j" L0 K0 l8 G ca% X2 R/ Y% ?+ I" E. v R
set max-grain 50! N3 k: E: O; q! j1 a* V/ g) j
setup-patches* l4 g+ E5 @' M
setup-turtles9 B( l2 A& a# F3 }
setup-plots
6 J4 @* P) C. f update-plots
* ~$ [" t) E g Dend
6 T0 k4 K7 e1 ~2 Zto setup-patches
/ f1 r9 E' o* K, f* s- v2 y# ]! s9 R ask patches
5 H0 c- ]) _3 @) J [ set max-grain-here 0! T* T- M- q) y
if (random-float 100.0) <= percent-best-land% Y, H; O, G$ D: E: l
[ set max-grain-here max-grain9 Q ^* I. `* p& A! M7 D
set grain-here max-grain-here ] ]. Q+ U/ N1 T& s! h* e
repeat 5: `! I8 ?8 H0 k1 @" n4 `
[ ask patches with [max-grain-here != 0]1 z: ]9 t/ z7 m$ l
[ set grain-here max-grain-here ]% E9 x i0 x% A
diffuse grain-here 0.5 ]
$ o* v4 ?' C8 ~ c repeat 10
7 s9 V+ i' u3 ? [ diffuse grain-here 0.5]
: t" I5 e6 y$ F/ A ask patches
2 G+ u% X* O, K3 d% z1 l [ set grain-here floor grain-here
) Q5 y4 A5 k: C! B/ z5 H5 f& a. l set max-grain-here grain-here
& O r" S9 C5 S, p" f) e& a' Y recolor-patch ]8 L1 p, y3 V/ z: k, {" E. b
end9 h% _ w3 p* ^
to recolor-patch
! A) @) M$ g7 _* B$ @3 w7 }0 T set pcolor scale-color sky grain-here 0 max-grain0 j1 I) G% c' K+ V% y
end. B- a2 x8 x2 D Y) t& _$ E5 c
to setup-turtles( o. @3 A; A$ {3 H
set-default-shape turtles "person"
+ C# f8 M# ]9 K; O; i* a. U5 @ crt num-people+ H5 R8 E9 E( B% }7 r( g
[ move-to one-of patches
% a# `0 A; z* {5 S3 G set size 1.5
* D& ~, ~: _; y- M- ^ set-initial-turtle-vars-age
4 d' L: p' [* W1 l set-initial-turtle-vars-wealth8 m; y, V5 @4 w6 Q/ [, a
set age random life-expectancy ]4 X3 V% L* ]3 I7 X/ q
recolor-turtles
1 i' w* |/ X+ J: Gend
g7 g$ i4 K) L/ \: I3 P3 C
" O- z: z' b2 v2 X5 vto set-initial-turtle-vars-age
; y. @# ]. t: T- B2 { let max-wealth max [wealth] of turtles
# s; g; T/ w: `& f, e! u3 r( u1 v$ \ ) s; n; D7 a; ^/ n
ifelse (wealth <= max-wealth / 3)) z) T) l$ T5 e/ @
[ set color red
. A" K# t# N. } set age 0
8 t% N9 U# J5 m! q: I* l/ Y face one-of neighbors4
! a% }9 @% C* ]9 \ set life-expectancy life-expectancy-min +
. z3 y( S/ |1 k) C8 [1 Z9 P random life-expectancy-max * N+ ]. C. }$ S8 g+ G# s" M- S, _
set metabolism random 1 + metabolism-low
% z6 f5 M; E( I' G' L3 P" @ set wealth metabolism + random 30
/ e) Z3 W/ e$ w set vision 1 + random max-vision
! z7 W$ l/ L+ V3 M set wealth wealth + Wealth-inherited-low ]
* j! {/ ^. I. L& Z [ ifelse (wealth <= (max-wealth * 2 / 3))2 q1 z- S' s2 C" v- b! \( v( W
[ set color yellow ( _. v- t# j/ r) O, U/ X* K& ]2 z
set age 0% i0 Z P+ }% g
face one-of neighbors4
3 j9 N I$ c5 q$ |3 j3 w: }6 ^0 k set life-expectancy life-expectancy-min +/ L1 G, `6 K5 `# v
random life-expectancy-max + 19 O- R! m7 W4 ?# P) x; W
set metabolism 1 + random metabolism-mid
# c5 l+ | I* }( T set wealth metabolism + random 30% Z; v, U6 R2 ?' o: I
set vision 3 + random max-vision
% l2 v, k4 p1 P7 x set wealth wealth + Wealth-inherited-mid]
: n/ ^8 f& T; }/ ]0 j3 d/ ~/ J [ set color green - ~% `8 n2 G4 h
set age 01 a1 S: I) p$ p0 Q/ Q
face one-of neighbors4 # ]5 @7 Y. C# U; V, P4 n
set life-expectancy life-expectancy-min +
6 j' @5 O" G$ R' r3 p1 \; h. ~ random life-expectancy-max + 21 c* h1 z+ C; s; U# U$ i2 K: x. A+ X
set metabolism 2 + random metabolism-up
8 g. f N; ?$ A5 ]! j) f E6 _4 [& d set wealth metabolism + random 30. d8 }' a3 W3 {% y5 P8 u' n
set vision 3 + random max-vision
1 a0 R' ~! Y; h- ~ set wealth wealth + Wealth-inherited-up ] ] 9 b. G: a+ o$ s3 {
$ k5 m# h4 o9 Hend0 C6 t' p4 ^* g, s7 z& P
to set-initial-turtle-vars-wealth
# _8 \1 v. P+ u& O9 p let max-wealth max [wealth] of turtles8 |3 f0 i# \9 B9 Y7 @
set age 0
3 D( m' s1 k/ f% a face one-of neighbors4
8 _) T. _' _/ G8 y$ r set life-expectancy life-expectancy-min +
1 f; o5 x% z9 N Z E- K# B" T; O random life-expectancy-max 4 ]6 ?3 b0 ?& Z I$ i; g6 k% v' h
set metabolism 1 + random metabolism-up
* u2 ] q. P7 T set wealth metabolism + random 30% Z; Z* z, t! ?, j w4 H* J
set vision 1 + random max-vision
* X( |. W6 }7 ^; X5 ^end }0 ?$ v3 Z: D; a1 n
to redistribution1 n0 Y$ Q/ f( i: j5 J
let max-wealth max [wealth] of turtles$ [+ q8 F. }% a
let min-wealth min [wealth] of turtles& C% R& o4 i* E2 W- c+ V, C9 ~8 J7 b
if (wealth <= max-wealth / 3)
x5 E$ N- a) o [set wealth wealth + Low-income-protection ]
7 ^ `1 y- L# U7 y. F9 C" Dend3 ?7 @2 d; d/ o1 X
" e$ W7 d( v/ R
to recolor-turtles: G! y5 B! v: t" C
let max-wealth max [wealth] of turtles
; w1 _- K0 ^, w+ M3 B) X5 ` ask turtles
0 l# ? P" Y! w% K: n, `, e [ ifelse (wealth <= max-wealth / 3)
w" R" q2 O" r& f, q1 l [ set color red ]
* d; R& ~, p+ |3 m; X8 q+ K [ ifelse (wealth <= (max-wealth * 2 / 3))
) v5 ?* ^( o" T. H [ set color yellow ]% `" {6 w. }: o7 L0 O
[ set color green ] ] ]" k- a8 _" y+ b7 V
ask turtles [ifelse show-wealth?6 C3 E* M; u* p6 T% O8 a
[ set label wealth ]
3 O# S( Z0 q' ^# j! s [ set label "" ]]
4 u% i1 Y4 E) K% {, f& pend5 H/ [& l+ b6 J9 F
# d& o( I8 z+ u% ]to go9 h% U. [$ z) v. u* w5 B2 b1 V
ask turtles
/ j+ z6 k5 o* q# G# S: h) \ [ turn-towards-grain ]
6 l+ J3 {; o7 h: {/ E7 Q harvest1 _5 X+ ~) ^5 q- O* U) [
ask turtles
$ N0 ]5 {3 `% ]0 \) a. I [ move-eat-age-die ]
( k' d; ?. w- t4 P recolor-turtles# g: s5 G; u9 g% J4 v5 t0 d( E/ R
if ticks mod grain-growth-interval = 0
, |6 V n1 s& J" s ~# P) ]) `& k [ ask patches [ grow-grain ] ]6 L. A- N) \- s3 d; L. w) ~7 m9 e
+ r3 K. j q/ G7 v( }
if ticks mod 11 = 0
; Y" O$ Q& X( M [ask turtles& X+ b. I; V" O6 Z9 J& f- q
[ redistribution ]]
~9 K/ b3 y3 l) L! y2 o5 u# | if ticks mod 5 = 0
4 U1 i: m$ Y: N, v [ask turtles
& W6 H3 V9 f( L8 s$ \' { [ visions ]]
! E" r! C( \6 U" `. c) Z tick [( _' s7 P" c! l' _- a, c
update-plots. R+ P+ ]0 A: v7 {- \; K- `9 v
end. N: g7 W& m( ~3 p- @
to visions, c" P3 R3 p+ R4 t
set vision vision + 1 ) C& k+ Q- F) A" V, E# L) |& [
end
& D/ H; N4 I+ T9 g8 w, D/ a
1 A; [' `2 }- F% `- A* L5 j" R! n
. g5 F) F L6 i, c$ q$ o" X5 l3 Q% L2 p8 n0 P3 t5 L- Q" ~1 ~
to turn-towards-grain
! @+ w! A6 s7 q set heading 0: _' ?! l% S; S, R' u4 g/ D$ G
let best-direction 0
7 i3 {4 g2 v, \( M$ e let best-amount grain-ahead
: b$ w9 S" _: C set heading 900 e; _9 G; K. s; r" D) q
if (grain-ahead > best-amount)
: h6 ]2 @" O2 z0 r! F7 T9 } [ set best-direction 907 o8 [( ~0 r- K4 e' b' F' G
set best-amount grain-ahead ]: Y+ ?" m. ^1 G6 X' k' t, y
set heading 180
4 I2 O" ]8 Q0 _+ r/ H, } Z' B if (grain-ahead > best-amount)3 B ?5 y1 I3 P& z# j) V9 E
[ set best-direction 180
3 }' }0 ?& d% N& ~6 m8 a set best-amount grain-ahead ]
1 ~9 {9 E" k7 I) [$ V set heading 270( U% S$ x7 `2 h$ M; o: J
if (grain-ahead > best-amount)
+ q k3 L, R2 |7 {! s [ set best-direction 270
6 r8 x, f9 y* x' J+ }/ |1 f set best-amount grain-ahead ]5 [$ }( v1 }; E
set heading best-direction Z P2 L B. u# D* A
end) l `+ `) [+ g& E
( u V: l5 U7 T. q, y/ v# Y: R
7 V8 z1 }! ], i, d1 Z S* V6 K
to-report grain-ahead 3 M/ Y/ w8 s( L! F6 |. }
let total 0
) |: j& I$ W, p! H let how-far 1
- E- E' J; o2 \. @) r repeat vision
5 n. w* U4 \8 Q- y( m/ | [ set total total + [grain-here] of patch-ahead how-far* `5 A9 {1 D' m. C. J$ T
set how-far how-far + 1 ]* W s9 \5 ^; o6 q
report total0 N6 C# {; _3 Y( D1 F
end0 n) ?! s+ R& w& n3 `
. W$ j- p; {: {* o% ?& j% Q1 W
to grow-grain
" U' P, \& Q4 c" n% y$ n+ ^+ }: p if (grain-here < max-grain-here)
& P9 i. B* s' A8 y2 @, ~" V' ~ [ set grain-here grain-here + num-grain-grown9 v* T( s5 z7 H+ h: m/ G# r# ~
if (grain-here > max-grain-here)
# w* k O. e7 d! g& M8 Y# a [ set grain-here max-grain-here ]7 }) S4 ?# U. ?0 ]9 X
recolor-patch ]
4 M/ } a# o" q& wend
4 z& J& `2 u8 i" M) r Ito harvest' k" l9 x; H8 Z! O
ask turtles
' d9 I8 j- i. n2 i! h0 c [ set wealth floor (wealth + (grain-here / (count turtles-here))) ]+ V$ Z7 \4 R2 j; L6 P* s+ r
ask turtles
z8 d3 ^6 R" M5 r6 ~ [ set grain-here 0! L$ Q3 ]3 @2 M3 _
recolor-patch ]4 a9 t0 h# E a) Z! N
$ [" Q) O! b5 E3 ]6 q9 k
end
5 q) C! N- [0 n, z4 _4 ]
) j, I9 x. Z( q5 _+ y+ Q+ x( r& j3 Bto move-eat-age-die 8 d4 t" s" `1 h
fd 1
* q. R/ i3 I8 X5 [ set wealth (wealth - metabolism)
`4 o* Y& ?8 @) S3 g set age (age + 1)" Q+ X2 e0 }/ h( w2 F, ]$ ]
if (age >= life-expectancy)
/ V4 o6 c% z; z9 s! w9 ?: j [ set-initial-turtle-vars-age ], L/ w& A) Q3 x" n7 Q% _
if (wealth < 0)/ N' U0 P/ e1 C* f
[ set-initial-turtle-vars-wealth ]0 ]( G9 A. g4 v" A/ {. I) m
/ h2 g. L) e$ ?$ `: ]8 \1 Uend
6 `0 v6 @# J' K- |/ l9 b( F) V8 T' b S, e6 R
6 l3 @, U& O1 f0 Y& u; }) R
to setup-plots" x( V/ L2 g s# S0 X
set-current-plot "Class Plot"
4 z b. t& h/ u P G1 A" p set-plot-y-range 0 num-people
+ d3 t' \7 X, C f' p. ^ set-current-plot "Class Histogram"4 O9 x4 P. ?- E* R
set-plot-y-range 0 num-people
* z8 q- B' @+ y, H+ Vend: ]* }' X) u! w+ ]
, W {" ?# t5 k/ M: B* N
to update-plots: t c: T" N. b. A2 [# y: G+ s; Q
update-class-plot
! ]3 H# X, V7 U* V& i; x update-class-histogram
- y B F4 T( i" a* P* a5 y0 u update-lorenz-and-gini-plots
3 a3 j, Z" F' \1 j# \end
! Q u& A) Y) R( C$ y. F* K
: ~8 N3 m- `6 v2 ]6 N% q- Tto update-class-plot
5 B, R" R, e( Q set-current-plot "Class Plot"
/ u% N% m' j3 ~- \5 P3 O: B, m U set-current-plot-pen "low"1 S" U! Z; _5 o C+ t
plot count turtles with [color = red]
0 A% r9 Q4 E3 \5 l3 y* a J set-current-plot-pen "mid"( s: z0 L2 S. a7 N/ y" G# t+ |3 y
plot count turtles with [color = yellow]2 c3 o- Q. G! ]
set-current-plot-pen "up"* C3 V5 o$ q' \3 ]7 R! p% B$ ~
plot count turtles with [color = green]) T8 l* Q$ \" @) j+ Z I2 @9 b/ X
end: M8 C& o4 b1 M% X- @' `0 m! V8 [
. C' P# e. [. Rto update-class-histogram# `% ]1 h* K" I I3 W X( m2 H
set-current-plot "Class Histogram"
& X" N" ~' q- _ plot-pen-reset
' a& m' D% @6 D! b+ \& \, p set-plot-pen-color red& ?$ c& Z. j- k, S4 L) T
plot count turtles with [color = red]/ L4 U e- T/ Z
set-plot-pen-color yellow3 R' h) _$ P; D
plot count turtles with [color = yellow]! L8 v8 u4 @9 b4 O& U0 f4 q
set-plot-pen-color green
' T: A( d S8 r- F) O plot count turtles with [color = green]
7 j. ]( E/ }5 d: zend0 k' v* N# @: M* L) h0 q
to update-lorenz-and-gini-plots: w- C' J3 S+ U
set-current-plot "Lorenz Curve"
2 P) x- R" c- G& `9 `# v clear-plot1 R' a3 k/ x6 S! {; d; L* G
* i; y4 F& y7 W$ B) J8 i7 p
set-current-plot-pen "equal"
; F+ s1 i7 R9 V% K; Y; y: c plot 0$ w- d2 S, Q7 V% g2 X5 A! Z
plot 100
6 a$ L5 I" @. R4 W5 @" B, n
$ h/ [9 B( S! O: _1 [, T" X9 q set-current-plot-pen "lorenz"9 t$ T- t, m( O& d: r% D
set-plot-pen-interval 100 / num-people+ p4 S5 i1 l. w" ` S: t
plot 0) P% i9 t5 N4 A9 m; c
2 [/ Z# A O+ g% E/ Q let sorted-wealths sort [wealth] of turtles. C! e6 d- k! Q9 @) H" }$ T
let total-wealth sum sorted-wealths
" G) {6 {+ w. t* m/ {( ^ ]5 t let wealth-sum-so-far 0
6 g- d0 |' F6 w# n# }5 j. o let index 0
) _3 x6 x6 F' _( s; g9 t, H' ` let gini-index-reserve 0. i: @: k6 x+ |# J( Y
2 l0 j! a x, R* ?- r2 @5 W
repeat num-people [* b( A) W6 d3 L; y9 u
set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)
9 H N4 X, y7 @% y plot (wealth-sum-so-far / total-wealth) * 100
. _; D, l5 b( q! J set index (index + 1)
; F) }0 ^2 X! x4 O set gini-index-reserve' r( m9 v* ]! j3 \
gini-index-reserve +
' k5 C8 V' `# ~* P S (index / num-people) -
6 d2 D3 r U0 c8 g* s# L (wealth-sum-so-far / total-wealth)
% a9 ~ Y1 F) }7 Y2 P# |7 ^ ]
% M: t s# L6 `1 q( c# n+ m4 x9 B
set-current-plot "Gini-Index v. Time"
* Z& z) K* }: g" Q! C8 p plot (gini-index-reserve / num-people) / area-of-equality-triangle
* A- C# a: r, bend2 u: L3 H9 Z6 Q# H7 c, B: Y0 V5 ]
to-report area-of-equality-triangle
! n1 ]# J5 J- h& b- Y4 O3 ? report (num-people * (num-people - 1) / 2) / (num-people ^ 2)
/ S: w- \8 y; I* X; {& Fend |