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
8 ?6 U4 u9 N: V' q4 {. Rglobals1 H7 `( P9 C* P% Y- }' B
[
$ n& i6 Q" ^; E* x3 r K max-grain
$ _3 N# O- f% { I4 [# r% E2 l4 |, G
]7 _6 _& X; r( `& @$ p' q+ Z8 T4 ?* M" ]
# W4 x6 t3 j% Z9 Tpatches-own
( v5 w$ _. t7 k5 o; z+ s[
* d- p. a# y3 J8 l! Z2 B" }0 p grain-here
2 h3 N5 ~6 g- \5 \3 [+ R! l max-grain-here
# h7 @; @' X* g7 s% Y' B]
- e" t0 ~+ r: g6 U9 _' r1 ]. G# X; X7 c
turtles-own2 \# g/ f, Q9 d7 b1 [% {
[+ Q& d" @3 E" Q+ E% B; E
age
[- D; e; [$ g# a6 I3 `$ o wealth
1 k- R8 i. v; x* T6 W: r life-expectancy
+ _, j; ~- | c. A$ `, R# C metabolism
9 \3 v9 `9 M0 S) q9 x* D vision
" M) j6 ]" `* _5 T0 q5 U inherited
! ~8 j5 l( c+ _5 F" P5 o h% p/ U]
5 z( i8 R+ o6 X1 a& w1 c( }' W+ S8 e/ ^. f4 f, P6 `% T
! j- {1 g. c. @# b* B) [to setup
8 @3 d% N9 D$ T ca
8 [/ q9 v: k$ p) _7 G; L4 t9 g set max-grain 50
' y" v4 z5 K1 d2 F; M setup-patches
W: O# M" n( D" b7 M setup-turtles. E- O w) L. D5 ]' I& X$ V$ F
setup-plots5 n! x3 w; V4 K- a- [- Z; }+ o
update-plots' M' C& O' d' K) g/ p
end8 G) c2 h3 B; x9 \% A3 t% G
to setup-patches) n4 F6 h$ @8 c3 l
ask patches
. \2 W6 M+ \! }6 Z [ set max-grain-here 0- L+ T- T; q l( P; Q* N% J
if (random-float 100.0) <= percent-best-land( j5 F6 w) ~7 r [5 Z$ I2 ]; u
[ set max-grain-here max-grain
" R, d5 G# `: [* Q( h/ S set grain-here max-grain-here ] ]3 }! @8 m v: l2 g4 z% b3 E; E
repeat 5
3 e+ ^2 f' y5 K6 B5 ~ [ ask patches with [max-grain-here != 0]
) t8 c7 I' O' e( h6 P6 F; I [ set grain-here max-grain-here ]. Q& a g. b, s/ z4 [' a2 g
diffuse grain-here 0.5 ]
5 g. P1 Z; o6 b, p7 w4 U repeat 10" |! M D" W9 L# W% \
[ diffuse grain-here 0.5]
! @9 ^4 q; I* v+ {5 J ask patches
; K/ M3 O1 S5 h/ b, E( F* d, H [ set grain-here floor grain-here + I; s6 c( O$ r. T7 m* H8 u+ d/ R
set max-grain-here grain-here / |$ W/ j' C+ t' d7 \% O5 A' S0 n
recolor-patch ]& ~# f; ~ A: g: x: ?
end
, M5 u2 O P& D/ t7 B5 u) S$ Wto recolor-patch
. }$ F% r& H' |1 Q- e6 O set pcolor scale-color sky grain-here 0 max-grain
' j x+ b& y0 Y$ S* H) Zend
; N4 P: z5 X! a& N; I% [5 Yto setup-turtles
1 r9 d* J& l( [9 C; ] set-default-shape turtles "person"# P# Y) a% d5 M2 j- S* h( O
crt num-people+ w1 u3 ?1 U0 P5 G: }& l
[ move-to one-of patches
4 x. X' Z& e% p& o9 _ set size 1.5
& Q+ ~8 M2 s. v& I/ _/ D set-initial-turtle-vars-age
! \2 A5 D, i C V set-initial-turtle-vars-wealth4 w$ i& W) N. `8 b# P0 [' C, }5 u
set age random life-expectancy ]3 F- l1 O' j& S* D0 G# X& M" m+ A' T
recolor-turtles
# [/ |5 ]# ~4 T& I2 fend! [( G3 a' P4 ]0 E* W, J! w$ R
3 L/ S/ E0 S0 W1 w
to set-initial-turtle-vars-age
2 D7 u: }0 C+ _- p: @0 a* b let max-wealth max [wealth] of turtles
4 A5 `" V l @$ k# h
! f0 Q1 }( I7 [. }0 ?4 a4 z ifelse (wealth <= max-wealth / 3)- x# e$ j$ M+ K# f5 q g) u/ v( E
[ set color red $ ?$ Y) O- \; B, N. I
set age 0- m, p$ @2 M7 s5 P
face one-of neighbors4 4 h4 \4 f" j8 m* J" @: F& g
set life-expectancy life-expectancy-min +7 u% d6 S+ j Y) v$ U4 D" I T
random life-expectancy-max
- ?: D2 p0 @4 l& E* O7 O set metabolism random 1 + metabolism-low1 [' l4 F( u$ N. W7 `
set wealth metabolism + random 308 ?3 T3 g* R& @
set vision 1 + random max-vision6 U2 `1 z5 \1 \8 H
set wealth wealth + Wealth-inherited-low ]) p9 q7 X! R3 r! L; [( V7 V
[ ifelse (wealth <= (max-wealth * 2 / 3))
) g7 i7 J0 g! o- n% G$ ] [ set color yellow " s/ Q, T, S& e0 _ l
set age 06 q3 n1 D* u; k3 a
face one-of neighbors4 ! y) R0 T) L4 M7 G
set life-expectancy life-expectancy-min +
& Y9 @8 x6 V, G random life-expectancy-max + 1' l; n$ w, x6 I7 f+ G; @' r
set metabolism 1 + random metabolism-mid
- \$ U& O6 K: h ~9 @ set wealth metabolism + random 300 j! i: q' ]9 G' H% y Y6 I" j- Q
set vision 3 + random max-vision
: e/ W6 u7 v) d5 y+ O) }, N: ` set wealth wealth + Wealth-inherited-mid]
- [0 F: Z! M; f- x+ y [ set color green
u- W2 } n! h. A9 u7 [ l set age 0* u# W8 I& F1 S/ l, v8 T
face one-of neighbors4
. ?+ W0 d# c4 c/ Y9 |& ?+ n" N set life-expectancy life-expectancy-min +
. g7 \ _! ]9 v; e4 X random life-expectancy-max + 2* s1 O9 ^3 A3 D3 c+ {& }0 ~
set metabolism 2 + random metabolism-up
S7 T. K9 t0 B5 f set wealth metabolism + random 30
, a o: X, y9 ?% z set vision 3 + random max-vision1 O" ^1 \% F% c/ U6 q8 c( E
set wealth wealth + Wealth-inherited-up ] ]
# P1 C' x+ C& q& Q 3 E7 j; C" C0 H! K& A# `. F
end' S! N; |8 E7 x1 G% `* P/ d
to set-initial-turtle-vars-wealth
" T; \, r( j6 T' a. @8 L let max-wealth max [wealth] of turtles
- n4 M4 m+ p2 C/ |6 O o set age 05 _- G6 ?8 {+ J( B$ g7 J m1 ~
face one-of neighbors4 ) H, p" ]4 \- ~; c
set life-expectancy life-expectancy-min +
1 g; J3 E1 O, t$ U7 w0 d8 L6 f random life-expectancy-max & P0 `+ L" Z7 c1 o/ J& W# N! O
set metabolism 1 + random metabolism-up
, j0 U* Q1 G: c; m% v- [9 C0 c$ f set wealth metabolism + random 30% n7 z3 i, P9 h: x& r. w/ f, ?9 d
set vision 1 + random max-vision
. @+ y- _0 J) D: i: }end
2 L9 ~5 ^, `5 a) nto redistribution
4 M8 G& V: ~. T% z+ t2 Q$ Wlet max-wealth max [wealth] of turtles
8 z6 D. \- |# E7 @( qlet min-wealth min [wealth] of turtles
- Z& r7 _6 ^' r( u8 q% x' Cif (wealth <= max-wealth / 3)
$ K5 u- w$ @' Q+ n6 H. G# \% ]: l" ] [set wealth wealth + Low-income-protection ]/ ^. B& M5 M: b8 y
end2 W$ o8 L8 G2 |* Y
7 i2 R9 m7 l5 Q Q$ Oto recolor-turtles* k8 q a4 K4 k( x
let max-wealth max [wealth] of turtles
7 X( }1 i- P# v; N+ P ask turtles G7 X7 L+ g# V5 N1 ?. U/ N/ C
[ ifelse (wealth <= max-wealth / 3)1 v0 z9 T9 S0 `2 S. B6 w6 Z- |
[ set color red ]* e* `$ J& O" s. X3 A- S
[ ifelse (wealth <= (max-wealth * 2 / 3))
5 r+ r, p* i/ b; l! H [ set color yellow ]
* Y1 @+ K. F9 m! d" I: _ [ set color green ] ] ]6 q& E! {& @9 c2 P. L3 T8 t4 ?2 t
ask turtles [ifelse show-wealth?
' _1 \; d8 j3 _* N* b [ set label wealth ]7 k' P$ g3 O y! J+ R% Y+ P" n
[ set label "" ]]
% [# |9 }1 o2 @+ e3 Rend
! U, Q2 Z1 ]8 M
! s* g0 Q% G$ m1 w9 N% X& fto go
. Y5 q# P6 S7 z4 o1 @" ^' q# ` ask turtles
% r7 L8 a: b5 S( b8 u) F [ turn-towards-grain ]
& R' Y+ W( T, p, T$ Z harvest! b, J* [3 [) Q p+ A3 }* h7 v. @& V
ask turtles6 U- [0 ]% M$ P( M
[ move-eat-age-die ]0 O/ v+ d; b; t2 _
recolor-turtles$ Y( T/ ?" a* L- }" g
if ticks mod grain-growth-interval = 0
" k. s5 ^7 b- q [ ask patches [ grow-grain ] ]
" s2 V+ c* ]8 F3 O1 `0 W, R9 f
5 L% k! P2 t! v1 ] if ticks mod 11 = 0
9 k: V4 q) s' J: y5 X [ask turtles
+ g& e5 ~/ a$ R) v" R5 p [ redistribution ]]% N; _: W5 W# _. A2 g( n" j2 y
if ticks mod 5 = 0
3 Z8 H6 e/ F, U* v6 x [ask turtles9 z, Z ~" b: v+ r' ]" q( y
[ visions ]]5 _% ]" Q1 W, g+ i
tick
. {- _" z; _$ E3 C8 J update-plots
; Y( Y% {; l+ x/ H# N$ W( c& {0 V+ vend4 I& g- I% b, D1 `/ Q7 j( [
to visions
9 q, b, C# j) | J set vision vision + 1
. X, R! k3 r$ b+ i0 Qend
% @: Q$ M/ J( w; b8 A" p; E, Y; @; Q/ u
. Z: b$ o# {, O7 W( R' L
6 q% I8 E+ A: d+ M: `to turn-towards-grain 8 H8 q% O* o9 ?5 K
set heading 0
# @3 U3 {- k) J+ | let best-direction 0
' ^) t, ? n+ L. s( O let best-amount grain-ahead
3 ]+ U/ F- \2 \( b8 h set heading 90- j4 N4 ~! W, H; K& O& U& K8 P
if (grain-ahead > best-amount)# K8 r2 H/ G" ?
[ set best-direction 90
" n, Y& }+ O4 P& u( s: X7 _5 u set best-amount grain-ahead ]4 e- r4 z6 g* d2 [' I1 ]
set heading 180- l" z- P8 B6 I g; E- U
if (grain-ahead > best-amount)+ |4 R8 M; R6 J8 j$ x
[ set best-direction 180
. F9 c. B5 \. [$ M/ f/ Z$ w set best-amount grain-ahead ]' Q9 z+ I# S, I6 t, F! v% p
set heading 270; y) v: p' h; b$ \
if (grain-ahead > best-amount)/ E7 Y; [/ G7 F/ I( K
[ set best-direction 270% c3 m: \' f' U) k* y9 y2 ]; t
set best-amount grain-ahead ]/ v% p1 E7 o: E: F- ?& K8 T
set heading best-direction
- A7 ~/ v' i0 X- v1 V! Gend% e# O( k. {3 c
1 ?( {( j# k! r x3 |. r, v) g% [
6 e' D+ L5 R, l6 ]) o. R7 r' qto-report grain-ahead
5 _. }( w$ ` D6 P- A let total 00 w- p: F- f4 u9 R
let how-far 1! E/ i d( b" }* D' @$ j
repeat vision
! H! } Z! e4 T: H' C4 M3 D+ n [ set total total + [grain-here] of patch-ahead how-far
3 k+ o% q' |( p, q. K set how-far how-far + 1 ]' |% I5 R( z5 `- G+ H2 M3 L
report total
! t* v! o" ?: }+ N. w' Gend& N( c: V( I$ S( p/ R0 J9 _5 A
5 w% G5 b- @7 Sto grow-grain
" \6 ?0 n S! E& F: @/ \ if (grain-here < max-grain-here)8 n" }$ g6 a2 B- `1 W4 q
[ set grain-here grain-here + num-grain-grown4 b3 K1 h4 E3 l) f' g3 c' U
if (grain-here > max-grain-here) $ Q8 s) h3 U7 T$ }. r0 ~$ \4 g! Y3 Y
[ set grain-here max-grain-here ]
! E' d, Z0 |! h recolor-patch ]. ~" w% B! @" n9 M( h. {% Z
end
9 w9 T+ Z3 H) R) jto harvest* X3 b# Q- W4 O L( \
ask turtles
' v0 u9 [; e7 e* |) z3 p [ set wealth floor (wealth + (grain-here / (count turtles-here))) ], u$ O# U( u9 B& }
ask turtles
; [9 f( d9 @; J" l u F1 ~ [ set grain-here 0
; R4 V# |: n. D5 [ recolor-patch ]
/ W# G% b3 D2 o% q2 ?# [ 1 F% i; `0 _7 T9 T
end
! A) o" e: {3 ], X) b
7 j: i* `( \! K. W; A- A" f, eto move-eat-age-die
( K; P" a( f% O4 y% J# r fd 1( W+ u3 o1 Y9 e0 l$ Y6 H) ~* B! e
set wealth (wealth - metabolism)
! f+ K0 s9 K4 ?0 U e set age (age + 1)
% ~1 F3 V! Y! Q if (age >= life-expectancy)! W5 |9 D8 P# K6 ^! H5 e4 U
[ set-initial-turtle-vars-age ]6 D" c X( s0 z: k; y& D4 e
if (wealth < 0)
- T$ a' s' Q. g+ N* `5 Y" f* {' O3 ` [ set-initial-turtle-vars-wealth ]2 y \! x" c) u
W, g6 o0 l) N# _end
# t1 ], P3 s% ~) ~* r1 X( C1 j
# X6 l9 \( d/ V+ |4 o+ |
2 c, [: A+ Z. P4 Lto setup-plots
3 [9 E5 i2 J0 i0 j% i& ~8 M+ f2 C- m% j set-current-plot "Class Plot"
6 C( v9 n; D5 }- l set-plot-y-range 0 num-people4 b3 ^% v7 e4 n9 E
set-current-plot "Class Histogram"
0 j; E* P9 S% U1 b$ y set-plot-y-range 0 num-people1 x( A+ S+ H7 r- n; C, w/ d. t6 g
end7 B2 h/ w2 m/ l$ p9 h
7 U/ a9 ?: g6 g- N; P k& bto update-plots
a! V' ^' r. f update-class-plot) S2 T9 ?0 n+ y; i) K/ c
update-class-histogram
6 L: t; n! \3 x U" B# O( x update-lorenz-and-gini-plots
4 T4 H9 Z) R1 N3 |/ V# U. ]& P: Iend. J/ J+ c& o$ q+ x. B1 R
& u6 q9 O( w6 }& V1 H1 I }8 `; X% ~
to update-class-plot, s* q( [4 J) v* m
set-current-plot "Class Plot"7 J5 [1 a* F' z5 u
set-current-plot-pen "low" N* ^% t+ ?( w$ v/ E
plot count turtles with [color = red]6 o: s+ `- ]* R1 m
set-current-plot-pen "mid"- i3 o5 v9 p: Q
plot count turtles with [color = yellow]
* Y- d! ?9 H7 ~; g/ D Y/ \7 p set-current-plot-pen "up"
# |3 | Z$ r, [( y/ i/ H plot count turtles with [color = green]( z" f8 w6 k- R X P
end9 J, r1 ~* z8 q
" C2 o2 U" s; ^to update-class-histogram
1 k* O/ g: `) {8 B4 a8 { set-current-plot "Class Histogram"( _ v9 Y8 a5 h
plot-pen-reset
- {$ Y2 b' W+ `- S8 F& T8 H. u& r set-plot-pen-color red5 x% L" k" j' e) H. S' ^+ z
plot count turtles with [color = red]/ Y& y4 Y; z! z. E( }& ]0 F2 ]# R3 p& _
set-plot-pen-color yellow# x5 d0 b5 ?. V0 |
plot count turtles with [color = yellow]
) @* a5 {" C" b, b set-plot-pen-color green
4 ?8 D" n1 A4 l, k! z Q- L plot count turtles with [color = green]
0 b7 `* q# x9 @$ S+ G' p: I2 H' Kend
- t6 B: d* ^- u$ i2 N2 k& Oto update-lorenz-and-gini-plots
3 r/ F: M# U; d2 C1 O1 S set-current-plot "Lorenz Curve"
U% E+ D! a$ h* Q clear-plot
2 f# p* |: l% {& O' ?) O$ j: D: Q. M! }+ }
set-current-plot-pen "equal"0 N$ v! |/ n5 S) m5 ]1 W. R
plot 0
! h) C; z F5 k+ j plot 100" E. U2 u+ v8 U3 \2 E0 C
) w8 Q5 k: \8 V) B7 F set-current-plot-pen "lorenz"$ Y$ ?3 H# J+ r6 ~# g2 v1 t. H
set-plot-pen-interval 100 / num-people5 c9 Q7 M( o+ r% K& B9 ~
plot 0& p3 [: I4 W0 |) W1 |. x: v' p
4 a+ ]& }: ]8 ~$ v
let sorted-wealths sort [wealth] of turtles
# m" x- j( e, \% M9 ` let total-wealth sum sorted-wealths
! |" K5 i/ X j+ d let wealth-sum-so-far 0
, t* x/ z) f. N3 O7 L* r+ P let index 08 C' ~& r i$ H9 D6 W( _
let gini-index-reserve 0
h& T; B7 H3 g1 P. X
! L7 W* u2 A! k8 z" o repeat num-people [
9 i2 o1 r0 ~% T. c+ ]3 M set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)
5 V) Z$ \* K! U8 h plot (wealth-sum-so-far / total-wealth) * 100
% K/ u5 d. k4 [! B set index (index + 1); w; w; c# Z/ N5 E6 |! h
set gini-index-reserve
7 R- z8 ?8 S/ U' q0 Y: P gini-index-reserve +
) n* z& L/ j7 s (index / num-people) -
" {+ y$ } \5 i& M) `) q, K (wealth-sum-so-far / total-wealth)6 ]7 J& r9 |+ R2 `$ I
]8 ]# u: h( L0 Q" H0 F P
2 y0 y! f5 }7 K$ ~" Q3 T set-current-plot "Gini-Index v. Time"/ z7 [. F4 j" L B
plot (gini-index-reserve / num-people) / area-of-equality-triangle
3 y, D) K8 T1 s6 J8 V/ ?end
/ K" T/ R; R5 N# _/ K+ F7 cto-report area-of-equality-triangle' p1 [* g! j. K- }2 }+ o3 |
report (num-people * (num-people - 1) / 2) / (num-people ^ 2)
* m" h \. i+ c! {2 R: l7 s9 O& Hend |