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
% z- l- i: q: Y! U7 L6 rglobals: O8 k5 K% }/ i; v( V. D
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max-grain
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% a8 Z. C) ~& Qpatches-own0 ?& V5 t# g% v1 \
[
$ Y; x% o+ O$ @" s9 ~7 o. A grain-here
. w7 m0 Q9 t: J. R. L4 i' W( U max-grain-here " [: B z$ [% L5 ]
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turtles-own% z7 y2 ?! |" v8 ?
[: k8 e6 Z" o, p' n1 S
age 3 n) r. N0 R; L
wealth
4 h, m! t; r% a/ h life-expectancy ! e: L, F! i0 p+ |" x/ s5 T
metabolism
& k; @! G4 T) K6 s3 e vision$ R' j* h4 ?$ ~* }* V
inherited & E5 z' \ n `+ a) X; Y
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to setup
2 p& Z* D9 o+ y* m, ^% ? ca6 p3 }# q" J9 D# f. ?; ^0 u6 ~
set max-grain 50
( P5 u" \4 r; M/ J, D6 A setup-patches
( R! k) M2 S, ` setup-turtles
& |" W3 g* v" ^/ v! Y- I/ W setup-plots
9 T/ K& s/ L9 t# F. b3 L update-plots+ B/ M7 ~1 {# q& `7 Y
end
# z- I0 W3 y" i+ d, V1 a6 Xto setup-patches0 Q% D! O# D' }# Z5 h) o0 t Z4 s/ |
ask patches
" G; R: a7 ]! t* C5 S* ~2 _ [ set max-grain-here 0: `6 ^8 q; o0 j" @( c/ f
if (random-float 100.0) <= percent-best-land. B, ?9 g! P6 Q
[ set max-grain-here max-grain! O6 ^4 y* c: f% V
set grain-here max-grain-here ] ]
5 | v; A$ k7 X6 G* o0 c repeat 5
# J; Q' g$ p% G. a: b- F2 s6 B) C [ ask patches with [max-grain-here != 0]
5 z: f( h2 p+ ~! Y$ e& B# e, l% L" [ [ set grain-here max-grain-here ]
, I( O2 M" B, r; k diffuse grain-here 0.5 ]
) v* m+ V8 l8 f+ c6 h* O repeat 10
+ C# M9 M0 {8 z! v [ diffuse grain-here 0.5]
% w# q9 t7 {9 y4 H7 k1 U0 j ask patches
/ C& h. r* Q |4 _! p; ~ H( a [ set grain-here floor grain-here 9 U' D+ k" h# Z& I P% \' e: V
set max-grain-here grain-here ! G5 l' @) j/ f6 l3 ?
recolor-patch ]9 ?% g- J7 z" c5 P; J& D F' u* s
end% U1 c8 @ d0 f/ `+ J
to recolor-patch , ? r( a9 S& Q5 [- U: C
set pcolor scale-color sky grain-here 0 max-grain/ U( \- }7 n* c
end$ I0 [* ~: |% V& c/ ]
to setup-turtles& S: O* k+ w0 S9 I0 R
set-default-shape turtles "person"
5 e1 ^2 b$ @. T3 W, C; w/ z crt num-people
! T5 K1 { N2 ~5 } [ move-to one-of patches 1 B1 E1 u- X% p: N! _1 f) R
set size 1.5 " |, d0 ]' c; N* {: n
set-initial-turtle-vars-age# j5 Y q6 Z- @
set-initial-turtle-vars-wealth% L" x a" X: q4 T' t' O1 d9 A
set age random life-expectancy ]: Z5 [7 ?% W# l7 X
recolor-turtles
! O' f0 s' a @4 hend
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5 @4 Y; u# d. T; U z# _to set-initial-turtle-vars-age5 z- [4 t9 j! X
let max-wealth max [wealth] of turtles( k; ]' A' a+ k( L i9 z' G
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ifelse (wealth <= max-wealth / 3)! C P7 T8 W/ P; B* M" Q! {
[ set color red
0 x) h3 R8 v/ Y5 O set age 0
- A& U( P4 Y2 s u4 Z% K+ D8 z face one-of neighbors4 5 `6 U0 R1 A3 s
set life-expectancy life-expectancy-min +" j$ H/ ?0 f+ ?4 f6 t
random life-expectancy-max
v" z9 y5 C( N. k L2 _ set metabolism random 1 + metabolism-low- ?2 ^0 H0 @$ a h! J
set wealth metabolism + random 30
9 P) [. t4 F ~ set vision 1 + random max-vision3 C" {* w; F; @2 R) h2 q3 l/ Z
set wealth wealth + Wealth-inherited-low ]) a( H* y& f0 F" M; s" P4 k3 I/ d
[ ifelse (wealth <= (max-wealth * 2 / 3))& U3 v: y5 B. N
[ set color yellow 1 o" ]6 h& w* V; N4 C& X- M( `
set age 0
9 H! u. e+ D4 n: D face one-of neighbors4 ) d: ]; n9 P6 k
set life-expectancy life-expectancy-min +
8 o/ U4 P4 }: Y# W: O random life-expectancy-max + 1
! Q! S" j1 \5 N9 D7 ^! u set metabolism 1 + random metabolism-mid
( k" C. c% q9 I7 d8 ]5 q, n set wealth metabolism + random 30
* V2 H0 [) X+ j$ X set vision 3 + random max-vision3 Z( d, ?9 H6 W) O, J
set wealth wealth + Wealth-inherited-mid]' A: [! z& q9 l7 G
[ set color green
. l' `$ a: h7 u, V+ J; f set age 09 U% W4 L5 o; }# r- L& K" y
face one-of neighbors4 3 z f6 w. _: l) v% `3 j
set life-expectancy life-expectancy-min +* _% ^2 \% s! e! P& C
random life-expectancy-max + 2- [/ _" q* ]" U* |. F" T+ u
set metabolism 2 + random metabolism-up
$ x1 r) L% S; J1 J; j6 ` set wealth metabolism + random 30" ~ A+ l4 }7 S
set vision 3 + random max-vision
! F N+ q* N2 ^$ G; h! w set wealth wealth + Wealth-inherited-up ] ]
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end+ V- T$ n( F+ f7 b P8 v
to set-initial-turtle-vars-wealth/ I4 L6 u- Q+ Q4 M/ J
let max-wealth max [wealth] of turtles( ?. Y, D& o3 k7 c- F- F/ R
set age 01 n, f+ Z8 b1 F6 l8 M
face one-of neighbors4 i2 {. V- _6 {
set life-expectancy life-expectancy-min +
' T! P5 g. P% Q4 j4 y, c- M% ^0 `. y7 J random life-expectancy-max
8 W0 p, U, `3 q set metabolism 1 + random metabolism-up
- |& [5 u' J4 [9 Y: W. n set wealth metabolism + random 30+ D( u& `0 U" `9 ?% s! c- S
set vision 1 + random max-vision
: t) c5 a$ m9 [9 ~end
: d. G; t2 P3 wto redistribution: ~6 F% v$ N; Y( ?
let max-wealth max [wealth] of turtles
( z4 r. i+ `+ Ulet min-wealth min [wealth] of turtles* |- `6 o& s5 {, q2 D! y1 ^
if (wealth <= max-wealth / 3)
& y! t: i! T' q [set wealth wealth + Low-income-protection ]
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to recolor-turtles
5 p5 |: h5 [3 T let max-wealth max [wealth] of turtles' ?" C- ^2 Y& p7 w
ask turtles
1 s! ^ B2 v/ E& B/ a; F [ ifelse (wealth <= max-wealth / 3)
# D7 l$ q3 z* R0 c2 L9 j [ set color red ]5 {" w* D9 U1 w [
[ ifelse (wealth <= (max-wealth * 2 / 3))
2 I% w# H. V% d- l1 K* V [ set color yellow ]
5 `9 Y. K* \% a# ~, b1 t [ set color green ] ] ]
: A# e4 d0 A) s. K8 x ask turtles [ifelse show-wealth?
2 x( T* H _2 d) b+ a [ set label wealth ]- y$ Y1 v( v" v& u3 @# c
[ set label "" ]]
1 h1 ~4 i" N+ X A+ U N, K6 n) Vend
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/ N- h. S/ E1 |2 ]4 k. V8 Ito go
# D; {0 ~9 W- b& G ask turtles
: I: ~0 j* _+ g# b& S0 w [ turn-towards-grain ] ' [+ `: G, l- z! l: H$ I: ^9 V
harvest) L0 U8 r$ v+ H9 i9 t, I' e8 }9 _
ask turtles
- o! C: o" V' ^7 d! q* }5 J D4 [ [ move-eat-age-die ]
/ Q# b/ N1 V G9 R6 \) q+ |" T recolor-turtles! a7 A* n& F- T- {
if ticks mod grain-growth-interval = 0" ]% i/ ], c' R$ _- q, [
[ ask patches [ grow-grain ] ]
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( S, a" w# ?; X1 p if ticks mod 11 = 0
2 p5 f7 h; C9 @) @$ X9 W, z [ask turtles1 q3 O+ n& }9 I( m+ W& I# [
[ redistribution ]]
0 \+ U5 c* S K- Q& V- B8 n Z if ticks mod 5 = 04 Q( K1 P9 f- x
[ask turtles
! ~" l& }( c- s! T& X8 }" h2 G [ visions ]]/ a0 q& D8 k9 V E1 u
tick
7 Z0 ?# I; v: X4 |; Z `2 c7 P- h( E update-plots
8 q8 x/ P9 y1 X# I0 T; Cend
' Y R+ J" t) k% p" N1 y+ f+ G% O+ Hto visions
; v- @. q& R) w5 i set vision vision + 1
3 D- F) e0 t# ^ lend# D, c7 x5 L/ i3 Y( f
2 r) g) Q) A# l/ \+ p
i; U( a" K8 n0 m& z
i, E1 E' I' Z$ M1 sto turn-towards-grain 7 y r1 `2 A9 r/ [3 U: ]
set heading 0# L' ?/ S0 _' X) E2 j& A
let best-direction 0
/ `/ @2 p8 ?- ~& Q let best-amount grain-ahead5 P/ o' N: u) `' S2 D8 m
set heading 90
7 T$ ~$ W; e/ d" m8 p/ K if (grain-ahead > best-amount)" f: J* e. c: N4 o/ |
[ set best-direction 90
& f$ O2 }' t M, a set best-amount grain-ahead ]( j9 @) f2 s9 I
set heading 180
) i. R1 \; J$ Y4 N" n9 _7 ^ if (grain-ahead > best-amount): a# q( e5 o0 E" p+ H! d+ f u
[ set best-direction 180
3 Z$ y& o: Y8 k8 ~ set best-amount grain-ahead ]
' B) x& A+ J" ^; ^* g set heading 270- C, U1 l" l& @; r& w& @
if (grain-ahead > best-amount)
' i& r* @7 o. T [ set best-direction 270+ {2 q* h5 n$ ?6 P' V
set best-amount grain-ahead ]
! ~4 Q" D; t1 \2 M* g: C+ e4 _: B set heading best-direction, G n5 u2 j6 N7 r/ D: q/ p% e
end
( }( J! x8 r, c$ @ S4 f; S' T, ?6 J- C6 y% ^
) l/ Y( U' i- q( o. F: Oto-report grain-ahead
# ?* O- D. L# f, g& {! P3 W5 J let total 0
# \# C+ n* V; |& o; B let how-far 16 P4 R# ~+ j6 W. R8 p/ [% F
repeat vision
: s' y, A7 e5 |0 |2 G v% r& G [ set total total + [grain-here] of patch-ahead how-far; S+ N$ {; D3 }! M. g H5 c# {" L
set how-far how-far + 1 ]* U1 t1 y3 b9 q* c
report total
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+ M% P. ?# S" R! S* w
to grow-grain ; a5 y8 q* ^0 k
if (grain-here < max-grain-here)
1 M; Z9 V6 D2 b2 t. O/ z [ set grain-here grain-here + num-grain-grown
- c2 d. `2 Z0 p+ b2 h8 V; T if (grain-here > max-grain-here) 2 t W1 U4 ` ~9 n6 k
[ set grain-here max-grain-here ]
4 k3 Z+ k' B! P# \. g* i, E recolor-patch ]! ?, i8 b2 k) j( ?$ H0 R( R
end
% I _ j& z r. Hto harvest
]9 V: c" |7 ^0 ^, m ask turtles
% n& e5 }* X( q: H [ set wealth floor (wealth + (grain-here / (count turtles-here))) ]/ p- [' D5 c, y; w" [( q3 a
ask turtles5 Q4 W! J7 b; E, a7 j" Z% c! O
[ set grain-here 06 T1 \8 D q1 t8 H$ U1 E) x
recolor-patch ]& K3 r/ \0 N9 Z0 o3 S1 l
& T8 X: o( r/ M9 y
end4 g7 Z) |: Z+ g, z1 ]/ S* H
% |* _. `& N3 J; @& X0 k' m) {to move-eat-age-die + d. x& B0 t, {3 w1 A: @
fd 16 k! M$ Z4 L: @" @/ D6 p W
set wealth (wealth - metabolism)
$ e7 k7 u" o' O. C6 m set age (age + 1)! u6 Q( H" L w0 w
if (age >= life-expectancy)
/ o( t0 R/ E+ q [ set-initial-turtle-vars-age ]
; N" {* P7 W2 b. i6 O6 ^1 T% k if (wealth < 0), |2 e* J/ c. B% u
[ set-initial-turtle-vars-wealth ]
1 j+ j7 e- {4 M3 B6 @' Y! @ . y/ | X! Y& |7 D
end/ o: h% d1 y# x* i7 u
/ O$ c1 d$ l2 f
" p1 L1 O- s" k5 Z; E) ^8 h. S* gto setup-plots2 p0 B; k) ?6 b3 I( {. c
set-current-plot "Class Plot"
" B1 p- \$ C" b set-plot-y-range 0 num-people
- `+ z% }1 J, C- G set-current-plot "Class Histogram"; r* w" p9 o+ C4 X- H3 u
set-plot-y-range 0 num-people5 }- Q5 o* n* f) ~5 C1 T
end
+ x* Q ~$ [& S6 ~$ }4 A. f' d( K. a
to update-plots9 q1 p0 k8 l2 j- n
update-class-plot
2 k" Q+ e- p0 {2 K; Y# F8 Y l update-class-histogram! U- k+ R' A# |$ N
update-lorenz-and-gini-plots
2 W1 |# {/ n3 E& Lend7 O$ Y- w u/ e H4 w7 G9 ~
6 y3 v2 x5 ?5 c# C7 w% B( Y( y8 ?
to update-class-plot
) T" f: `% Y# e- g; j set-current-plot "Class Plot"9 S, ~- a) e' _! s
set-current-plot-pen "low"3 J6 |, W8 |% \
plot count turtles with [color = red]
6 E# n3 _1 g7 B. @! ^# y. B9 H" c6 U set-current-plot-pen "mid"
2 r2 W. E9 l0 I' Y U- o plot count turtles with [color = yellow]2 W0 T+ ]% ?% c
set-current-plot-pen "up"1 U' W9 a) f) A; w4 j8 u4 N
plot count turtles with [color = green]: W. V$ E [* _' g
end7 P/ `% z/ e1 @ o' H9 a
1 R& C2 D' f; z9 _8 m+ D5 ^5 t1 U
to update-class-histogram
1 j! E* u8 D5 E7 e3 e4 ] set-current-plot "Class Histogram"% C) s, r: ]: }' q6 N+ {4 k, t
plot-pen-reset
5 m2 G! c, _3 ?% d/ o set-plot-pen-color red
& ^0 o5 G* q/ j! K5 S o plot count turtles with [color = red]# ?( P. _& `( Z2 N4 _
set-plot-pen-color yellow
9 r( [( _+ E8 a( K% o plot count turtles with [color = yellow]7 P8 q9 c" Q" y. b: Z
set-plot-pen-color green1 N5 a5 R5 R7 a
plot count turtles with [color = green]
! G% @7 B/ x, ~$ y+ Nend( @& c' B) t& z% Y1 w* c
to update-lorenz-and-gini-plots
7 S. Q' b0 ]4 }1 ~$ N. X, s set-current-plot "Lorenz Curve"6 a/ U0 f: l" q
clear-plot
! }2 w' k, z7 G N; p$ s0 X1 @ L/ ?/ y, l% j* T
set-current-plot-pen "equal"3 {) N1 E2 ]" u( f0 D2 H% A
plot 0
6 q+ I8 e1 e9 O% e& C5 P% Z plot 100
' A/ S4 H' x _9 T; F- o, k2 o
0 l7 N% V- `, f5 Q set-current-plot-pen "lorenz", A& B& M" {0 C% l
set-plot-pen-interval 100 / num-people8 Z7 P% L( n$ Y: \; ^: z; e* r
plot 0
3 L/ q0 D, p7 q; E/ h& k# J- k$ n4 W) k; ]1 W! ^4 n
let sorted-wealths sort [wealth] of turtles
3 O1 R8 R, s" D O let total-wealth sum sorted-wealths# y w% `2 Z$ F1 h, c. \6 e$ Y' r
let wealth-sum-so-far 0
5 ?* k) h4 F& k% T2 \4 i let index 0
* g+ \5 g \6 N5 K let gini-index-reserve 0
, W# b- X" E' M/ M
; E, l- _; x+ b7 X& C8 ?. z repeat num-people [8 q: T6 z* f) n0 w2 h2 E
set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)
# A& I0 M; k: f, b% f& \* Y plot (wealth-sum-so-far / total-wealth) * 1002 w; [( f+ H5 g- {" G
set index (index + 1)+ c4 g1 L0 {3 V9 g2 ?7 t
set gini-index-reserve) ^( z! _% ?6 [/ F+ \( j) l
gini-index-reserve +
$ G; |! Q/ s8 o; i$ T4 A (index / num-people) -
5 B! Q" K! ?1 U: L& G5 T. C# D (wealth-sum-so-far / total-wealth)
1 \* u; k8 Z& {2 q# b ]3 Q: w, ]- y7 S* J5 w( K# p
- l, P" o6 J4 ]( r, M set-current-plot "Gini-Index v. Time"
/ v* s) `3 }/ Q% d plot (gini-index-reserve / num-people) / area-of-equality-triangle# L T" F7 f' k8 y1 C" S6 [
end- m6 T: L' `6 n+ q9 ~+ ]; b* {$ C
to-report area-of-equality-triangle
' s' M/ \6 R* H report (num-people * (num-people - 1) / 2) / (num-people ^ 2)' l& w( Z' f. @6 l- Z1 X9 F
end |