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! I( I) p& m; L1 d' Z( F2 }- w
globals0 d8 r1 V2 [9 X4 Q, \% Y$ G" d
[
1 l7 d" @& j5 O' B! o max-grain 9 O) n2 S5 o" S- Z, `! F
8 W6 l$ P2 v9 |& B! Z3 P+ j8 K
]. q) p6 d- i( g/ I% _$ ?
% ] C& A4 v# }2 q' |patches-own
L0 Q/ o( t" |, P3 F[
8 A9 ]+ Y/ t, l9 K grain-here
2 K$ F+ U: T+ C4 {" q. B- H0 s& w$ b max-grain-here $ \) Q. `, s: v/ B* _+ _+ b( s
]
" `0 ?& d, _6 ^0 _
9 V9 L/ B. @5 ?, Y# j. x" q( ~, Yturtles-own
0 l; s# x4 {" j% F$ E[
( _& y4 }, z) z+ k age & i) B R( x* M1 j1 }1 c
wealth
0 a9 n M0 s& x life-expectancy
+ D: @0 m6 g) r, P metabolism
- G1 p" u. S6 g2 c1 b vision9 p7 c2 `; e/ w9 s, g
inherited
4 f% a9 I9 X! A8 {]
/ o. X/ Y1 P8 k K; `/ u: k5 ]: H) _) N
v2 p. g9 e4 t4 |$ w4 x4 yto setup# n% u/ R( R5 X5 {1 D9 {
ca `0 U! @2 T9 s" y( w& M
set max-grain 50
/ H1 p- e# g/ Y/ A; b% U setup-patches
: S- Z" h. t* E8 g1 ~2 W setup-turtles
7 ^$ F3 S# @9 D$ w( f+ N1 V* b setup-plots
" w9 u+ l: }0 a* N2 }: |2 X update-plots
! S) l, D! {9 O* Uend
6 @4 M, J7 U* U2 Cto setup-patches
$ U1 `/ G {) ^# ~! @) Y ask patches3 R& q1 f" W7 U0 r/ o: G. X
[ set max-grain-here 0! ]& O! y# T; A5 ]/ u
if (random-float 100.0) <= percent-best-land
* d' E, y; P7 y7 s& [6 }0 s [ set max-grain-here max-grain/ e h: ^$ F6 `2 S3 N/ g
set grain-here max-grain-here ] ]
) j$ f& F4 X2 Y: w; Z repeat 5
$ m5 G" G7 _8 w9 a, b& E& k [ ask patches with [max-grain-here != 0]
6 i$ h0 k1 ? h$ P. u/ ] [ set grain-here max-grain-here ]
3 g7 _ o$ s9 O/ C0 P' m; @ diffuse grain-here 0.5 ]1 [4 F6 |( K5 @& h% F
repeat 101 k2 U0 q8 P/ {' p; u
[ diffuse grain-here 0.5] ) C0 u* {8 W, P4 G5 z
ask patches# `$ J" }, r3 D/ f# _
[ set grain-here floor grain-here
% r4 x- p; v7 A6 h set max-grain-here grain-here
6 K# b! L! m# p/ Q" [ recolor-patch ]
! q ^* R6 d. S) I& G( J5 Dend
+ w$ v3 z% C" ] N4 `: D0 lto recolor-patch + A" T( C7 k8 C( \
set pcolor scale-color sky grain-here 0 max-grain4 N( Q7 W- ~, ]$ Z3 d
end' X7 H3 _. M% f0 a4 E3 W
to setup-turtles L; Q/ r$ h( X/ D/ _
set-default-shape turtles "person", G- H- k- X; y# b/ i
crt num-people
- s' l& H# ^, i [ move-to one-of patches % P# e8 Y5 a1 q" ?# S1 C. V
set size 1.5
7 J+ D6 V+ E1 H set-initial-turtle-vars-age
( w# [8 _: m: g; C4 t4 j set-initial-turtle-vars-wealth. x% t2 h! K& a" A! O3 T. o/ O
set age random life-expectancy ]
$ I2 }( P! c- K recolor-turtles
! V0 B- y v! d, O" o! D* kend+ q" \( a) U/ F9 E, R
( n" e, r7 l: e+ s7 L6 e$ l0 J
to set-initial-turtle-vars-age
1 W0 l) z; o0 q' P& \: p let max-wealth max [wealth] of turtles
3 Y/ O/ q8 W; j1 a3 c* H$ D+ M& v5 \! \% I' E
! g2 f2 m4 G' b" j ifelse (wealth <= max-wealth / 3)% u4 k. ~9 R3 k }4 W% z5 A
[ set color red
# T1 y$ R; ^: U) Y4 t9 A- e2 r% j set age 0
) L' o2 V# \5 A. V face one-of neighbors4 0 I0 V% d& x- H2 w. D
set life-expectancy life-expectancy-min +
" r: e- k" P+ M1 J& J random life-expectancy-max & r' @ C9 w1 p! @; h1 w
set metabolism random 1 + metabolism-low
8 J8 v8 q q, \# m2 G set wealth metabolism + random 307 U! D6 n% b+ O: i4 B& U! S
set vision 1 + random max-vision
" b( W/ o) f% |7 X set wealth wealth + Wealth-inherited-low ]1 U* j4 K% N# w/ c+ I, M
[ ifelse (wealth <= (max-wealth * 2 / 3))7 \0 h! ^7 H9 C
[ set color yellow , [: L4 _, T( `9 G& E2 o) `
set age 03 N+ g7 B3 a/ T' m' k. }- ^- L7 y
face one-of neighbors4
% Q9 y1 V- U; ]' a set life-expectancy life-expectancy-min +1 R& B1 L# P6 |9 P5 d
random life-expectancy-max + 1
+ n4 ?6 y B% \: Z: q4 {6 q set metabolism 1 + random metabolism-mid% E- r3 k. G& `5 ]4 a+ f+ P. e
set wealth metabolism + random 30
1 U0 f- L* A7 L! z! _7 W set vision 3 + random max-vision2 {0 g6 o( \/ v) S u" Q, _
set wealth wealth + Wealth-inherited-mid]
; P1 h( g' e3 \. C+ U7 E X7 e [ set color green 2 h" N# v( w: ?5 B/ F" T
set age 0
) i! k) E! ]- l7 z& G. L# ` face one-of neighbors4 4 z! |6 }: o$ g6 l! H0 \
set life-expectancy life-expectancy-min +
: S* I, b% y1 }; C, k- [1 |+ m) W# ~ random life-expectancy-max + 2( B- c8 ]7 x2 s" C
set metabolism 2 + random metabolism-up3 Y: g( T' B' A4 z4 K& {9 P
set wealth metabolism + random 30) ^7 C v4 n. Z- Z: z8 S8 k; t
set vision 3 + random max-vision
8 L1 e5 N1 A$ z9 T A set wealth wealth + Wealth-inherited-up ] ] & P* |1 W9 u0 u1 n! l3 W4 s" U
. \7 {' J* Y; ]* R* Bend
% m) P( r# d" l" ?7 V, Rto set-initial-turtle-vars-wealth
7 O8 D& ], C( E( D let max-wealth max [wealth] of turtles; f6 M: d, ^/ I8 ]7 m2 D) m
set age 07 ]9 g' \4 R) W. i% `
face one-of neighbors4 : Q- v- a! I: x8 L3 t) Z
set life-expectancy life-expectancy-min +
) I, R0 f7 Q) I1 Z6 K1 E1 H random life-expectancy-max
$ t: ^, q; P2 w, v! B t1 N set metabolism 1 + random metabolism-up
! z, j o/ [, i& O0 _ set wealth metabolism + random 30
( V6 I0 ]" p) q+ w) d/ G# G7 R set vision 1 + random max-vision ; V" U& V( p- n- i4 z
end" X) L7 |- D. o3 g( v
to redistribution
6 |; Q7 {6 A( Blet max-wealth max [wealth] of turtles9 i4 b5 K$ j' }2 n; g3 v
let min-wealth min [wealth] of turtles3 E& U; m% u) @& }2 s2 e
if (wealth <= max-wealth / 3)) m2 s+ ]2 _* \1 d0 Z. `
[set wealth wealth + Low-income-protection ]$ ~/ M c G, S' g$ r- u, X3 S5 w# k
end {5 m8 U0 N# E" C/ l
% J" J, w Q* P+ N. a$ f5 U+ l r
to recolor-turtles
4 F& Q; B1 g/ Q8 n6 U8 e, }0 i let max-wealth max [wealth] of turtles
. E$ c8 |8 n9 j L1 {& c+ o ask turtles
" m8 K* B! w9 |: t [ ifelse (wealth <= max-wealth / 3)& ^: Y1 r( E: | p, P
[ set color red ]
7 T& x9 T. s9 g: k1 t [ ifelse (wealth <= (max-wealth * 2 / 3))& T7 m- I/ F. ^6 {3 G/ I V! _! R$ d
[ set color yellow ]3 I5 y) O# \( d7 r+ `6 o
[ set color green ] ] ]
" ^* j8 j1 [9 `- A. a0 G1 u ask turtles [ifelse show-wealth?
# O/ Q \5 Z k. i [ set label wealth ]2 V* F$ l6 D) |4 @5 S
[ set label "" ]]5 q- C# | t! J9 e' L* x8 R) m
end: w" g4 c/ K/ N B' }5 C# ?+ q2 h5 k$ `
" ~ Q' Z0 ]' p; r
to go
' p8 u+ l. k/ ^ ask turtles1 b( K: K4 w! m. N k# Z
[ turn-towards-grain ] $ p! q9 \6 M u x" d) `" Y. i
harvest/ Z( j. d" I4 K
ask turtles
& _' Z a- _) V9 m5 I0 _* U [ move-eat-age-die ]
9 Z+ ^8 {3 y6 \/ C0 Y) w& q3 ` recolor-turtles
/ C! f R' }' j) U. { if ticks mod grain-growth-interval = 0
* @5 Z5 P' p( @' c& K8 I9 o [ ask patches [ grow-grain ] ]
1 o2 H, ^/ T3 Z; w( V - u& v( T) S. P5 } Y& D& P1 ^
if ticks mod 11 = 0$ K/ _ I3 ^1 {0 C
[ask turtles3 f: Z( g5 ]+ |& {4 \3 n+ O
[ redistribution ]]
& ^4 x d B+ Z# X' b if ticks mod 5 = 0/ m5 @7 Q" E" }
[ask turtles
/ p5 ?$ }! X" v# v [ visions ]]. x8 Y v: O& R6 x% O2 k
tick, m! u- H9 h$ W' b# ^
update-plots
! z7 w$ ?1 O6 N/ ^/ yend
7 v9 J9 ?/ e. b1 ~5 Z0 M, F1 O: X. dto visions
. y+ x( \; U' V9 `: f8 t% J set vision vision + 1 . `5 X. Y7 ?% q" F
end% |& a( i0 @ M' n5 d
9 W1 `) Y; O- r. ^+ F7 B2 `1 l0 X9 _1 R" B7 `2 s* I6 ~
9 L6 `. q* H- B" E
to turn-towards-grain
! F; s5 C+ Z& e( N set heading 02 v) G) v! {0 s+ u/ k
let best-direction 05 j4 B7 \' K2 ?+ N
let best-amount grain-ahead6 F- C( b4 }8 h7 x2 D
set heading 906 v1 P4 E8 C1 [7 d+ {( k
if (grain-ahead > best-amount)
0 m q# l( Q6 q+ O3 J% C) r B( j0 h [ set best-direction 907 Q# D) ~6 O3 x( n% h
set best-amount grain-ahead ]$ ?8 i9 Y& `! t8 \ i# h/ V
set heading 180! z. T5 b: x. M6 m5 U( {( a
if (grain-ahead > best-amount)% S; T1 Y1 W) `6 K# H! X; R
[ set best-direction 180
3 q; F: P9 H& J9 q) o, j set best-amount grain-ahead ]
& [6 d2 O9 l; m" |/ t8 y set heading 270
+ ?2 w" e# ]! q! J if (grain-ahead > best-amount)! e/ o# {4 L$ t' ~
[ set best-direction 2703 V- E& @3 f7 B O+ R, u4 E
set best-amount grain-ahead ]
) W) F K1 O" C5 m4 j6 V s set heading best-direction& E4 ~' g( v2 R, o& U$ M2 _+ W" |
end
% @7 e5 p) A c' M- Q2 `+ ^: M5 c" {) l$ c1 W
9 \! `3 L: d. _
to-report grain-ahead
+ a: w, g, ]3 d- D& w5 X1 K- J let total 0
6 z! f( r# W/ H1 }: h let how-far 1
3 e& Z, x6 F/ f$ n$ h repeat vision" N/ d, H+ o6 ~1 T+ O6 ?
[ set total total + [grain-here] of patch-ahead how-far
: Q* d& G c) u& a set how-far how-far + 1 ]
7 x8 f" s7 s6 H3 K6 T) w6 o0 r5 ~9 ` report total& A0 g3 J: u" o* T+ j
end9 x, l) m" S+ w. x+ h* e% X
% n% O+ a0 y* r8 {0 t6 X3 w8 @
to grow-grain 1 j |1 X2 d8 z% x
if (grain-here < max-grain-here)2 W* r7 p0 P8 w: z* ^9 F# G
[ set grain-here grain-here + num-grain-grown
8 V/ g* }( _" q+ f4 D% u if (grain-here > max-grain-here)
) ~% L: t) k2 N& c [ set grain-here max-grain-here ]9 A" {' e0 X/ E ~
recolor-patch ]( `) n. M5 {6 o4 C5 A7 e; z5 L/ Y3 g
end
- w' A2 N" w* T; ^" z3 A: jto harvest7 ]9 x* q' g$ s) N1 h( \ z
ask turtles
$ y+ ~- D4 l [5 W1 K [ set wealth floor (wealth + (grain-here / (count turtles-here))) ]
4 o1 C8 r" G' x1 T. } ask turtles
* k8 D* j( s: B# J! k* y* V$ r [ set grain-here 0
9 k H* O& z5 L% ?# y recolor-patch ]; g4 I. I: g; F0 K
6 A2 j _! P6 y0 w- c+ d2 N
end) S. u" C3 g, d) C3 O [, t
# l! J9 | N8 z! Q1 [) `1 h, `4 W
to move-eat-age-die
- a! F/ a) @( O; ?2 H fd 1% P4 s( T) R1 T* }8 g
set wealth (wealth - metabolism). c5 }* u' a! ?/ n# q, ^
set age (age + 1) G( ~4 n( F+ L# @: C& C+ V
if (age >= life-expectancy)3 o! H4 e1 a! q' Z7 B: s
[ set-initial-turtle-vars-age ]
9 W2 }' W% W8 g7 m2 v if (wealth < 0)+ E2 ^( I( e, {. S5 \* p
[ set-initial-turtle-vars-wealth ]
4 b( q ~. T: d- C7 _ 5 a' q# I/ o! u+ b W; H
end
8 q# b- | q$ {" |* D* S9 r. B: r, a1 c, \
! H% C+ w1 g1 r; R
to setup-plots; g4 @3 H( ]0 a% ?
set-current-plot "Class Plot"+ B c! \' ?+ v
set-plot-y-range 0 num-people& Q9 X7 q: E* c/ b; j8 P+ l) S0 m
set-current-plot "Class Histogram"
/ [* S2 s3 ^# \# C3 n B: r set-plot-y-range 0 num-people$ k7 E O! e5 a1 T
end
; C! m* C( r2 Y
) W$ a/ Q9 `) j2 Y1 Z2 h8 ito update-plots0 F6 j- ]+ V5 l/ g
update-class-plot
c' V: U9 R: R+ H" V0 n- q" F update-class-histogram+ v# u% F( W3 y- m! {: k% p
update-lorenz-and-gini-plots
) H" @1 ?3 P4 _end
4 o: i1 k9 J. B# z" i0 N! E
: N7 R9 l z# Z: l! [# P d- Uto update-class-plot
8 B! S% n% o d! o" T set-current-plot "Class Plot"( t+ w3 C8 C. h- |
set-current-plot-pen "low"
0 q9 n& G0 }: g plot count turtles with [color = red]
7 J: w, a8 p2 V X set-current-plot-pen "mid"2 j/ W' I" k1 V2 |* ^) j# a ]* F
plot count turtles with [color = yellow]
3 v$ y) Z3 e% K ~% D2 D; W set-current-plot-pen "up"0 a. ^3 x- Q* m8 c4 U4 O% y1 H4 L
plot count turtles with [color = green]" t) w" M1 z2 I; X# d4 e' k
end
) G2 \+ X* \0 D" I# N
& i e( y$ v" v4 Hto update-class-histogram
9 Y& y# _% W Z5 H set-current-plot "Class Histogram"
: h g* Y0 I6 _7 \( j0 l1 F( _ plot-pen-reset
/ t, s+ {% r) q/ _0 [ v set-plot-pen-color red
' w' Z5 M2 M2 Z5 r! f4 H plot count turtles with [color = red]* b! K9 p8 I( d; u
set-plot-pen-color yellow& q7 O: U2 X+ s" t0 ]% f
plot count turtles with [color = yellow]: D& T# r6 B: a" ~
set-plot-pen-color green
1 f: l, o0 T4 |4 p/ F4 x plot count turtles with [color = green]
l) z' h: G" u& j' ?, Xend
" U- J8 i* f' W/ x* c8 Jto update-lorenz-and-gini-plots
) w! j: l1 k, n! a! Z g set-current-plot "Lorenz Curve"
$ O; R2 y8 t+ I0 p/ b# b clear-plot7 G1 j) ]/ R/ ] E5 U
- U! b- ]% \$ N6 r set-current-plot-pen "equal"
^. y# r8 `1 p3 K% `! |2 \$ p plot 0% m. J$ k$ A2 ?4 v' ?/ B
plot 100/ k. C x# j" p- ]# |1 d& ?, U
8 e0 {+ b% T% C: O$ t set-current-plot-pen "lorenz", b2 K6 ~: p% w
set-plot-pen-interval 100 / num-people+ g# {7 }" F- Z/ c; I
plot 0, O# K6 R2 m$ e- s/ f
; C& ]# m/ F. P6 u( g$ k$ @
let sorted-wealths sort [wealth] of turtles
" o/ `' ^: z( m E let total-wealth sum sorted-wealths
: J; }' d( {8 A5 ~) U let wealth-sum-so-far 0& O) X* \* W( d0 |& G) K! u# O
let index 0. a( P* _& a+ ?
let gini-index-reserve 0
0 {9 `& {% Y2 P% m- U: [ [: E; R, m
repeat num-people [
) i* S2 @2 \$ w) j/ {( \ set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)- C8 F' S: C# S `, H
plot (wealth-sum-so-far / total-wealth) * 100
- ~* ~% Y8 t/ D9 k4 x6 V set index (index + 1)
! R4 @8 i7 w/ k1 x set gini-index-reserve
" Y/ x3 w$ C, P% u gini-index-reserve +$ g5 s( x$ p) t( L ^# ^% f/ U
(index / num-people) -
/ ?, W% Q7 F/ U6 B2 w" l% H (wealth-sum-so-far / total-wealth)/ x% k* L( |1 f s/ L
]$ \1 k3 I- Z! v3 _- p0 F
7 C/ B7 a* ^ p3 p6 t7 r+ r% X
set-current-plot "Gini-Index v. Time"" F5 j ^# y' H1 n/ [- O }* b' V
plot (gini-index-reserve / num-people) / area-of-equality-triangle
7 n; [7 N% w+ r, ^/ P8 [4 N* nend
: X' E1 ` x: E; B# Jto-report area-of-equality-triangle) p( D9 v# h; h( I
report (num-people * (num-people - 1) / 2) / (num-people ^ 2)
- h$ g8 E* n2 i% E. M0 [% tend |