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( G/ G+ q9 L; r+ M* s! ?globals
/ @5 i6 r' I" L[
! i' r3 p0 E' X6 i) g7 w$ b$ c max-grain 0 n+ w% h4 y% h6 o, B
4 G' k+ b" w! {]
5 B+ u8 @9 f* f0 O* V% f5 w
% b/ n4 }1 a. Fpatches-own
8 G+ b- {6 q1 P0 d* [: m$ q6 }[8 M) `. }) H: ~: Z. ]" i" s* }. q
grain-here ' w. h) k a; Z" `$ p( X
max-grain-here 2 |7 p, P8 @ M5 X8 G, f0 M
]1 i) g$ {3 c; U
& U- M5 ?$ X/ j2 Z! H
turtles-own
7 U5 i% a; g! P* P[
% U$ L/ m% g! @4 o; ] age 8 B8 x% l3 R. n' b
wealth ! _4 F( }- u; b k
life-expectancy
& N8 f( Q9 n9 s6 a; S7 O metabolism 3 N4 p7 `1 R2 ~# ^# [
vision0 T/ h# w' O6 w0 g5 V
inherited
1 X2 d# O* u0 f) A" l; p* T3 k]
+ m2 y6 _. f* Z! A; I) @$ r3 @3 z2 x2 T
: @, }" Y j8 \ o' ^4 V( cto setup8 I: `. Y3 n' J7 T# N0 U
ca0 Q x# z- K' f( |! G4 F
set max-grain 50% U `6 d9 j; K" Q; X6 j. E x
setup-patches
) l4 F/ Q3 i1 i( M/ l5 Q: q setup-turtles
) _: ]2 c* k: Q setup-plots. \) H1 I2 n- u& t8 h- |% q" I
update-plots8 w( `: K2 [+ {& u
end
* g; m) k; ~+ Fto setup-patches
2 \1 E B" I- m% r! @5 X- @ ask patches
) _# @! j4 U* r" b) } [ set max-grain-here 0
9 l2 Q. }; U% }2 O9 R7 m if (random-float 100.0) <= percent-best-land9 |. ]+ E* U8 j- ?8 ?/ |; r
[ set max-grain-here max-grain3 c4 G6 |1 J8 I- K
set grain-here max-grain-here ] ]5 q6 e9 V4 Y/ `9 c
repeat 50 V3 I. d/ |, W0 T0 k* ^
[ ask patches with [max-grain-here != 0]# G) p( u) J; ]0 ]8 f- i3 h: r d
[ set grain-here max-grain-here ]8 @$ @. T3 ^# w
diffuse grain-here 0.5 ]
( P8 \$ I& b( H2 u" w repeat 10/ h0 t! b: p9 ?2 I$ ^( o& D; t
[ diffuse grain-here 0.5] & I$ ^7 t' X4 m% l
ask patches
4 X3 n$ i2 T, V" w" e3 h5 K [ set grain-here floor grain-here
* ~+ a1 r. T6 P) h/ ? set max-grain-here grain-here
k. m3 D6 C; J% p& A& D recolor-patch ]
) s' s* z5 v, a1 [3 qend9 v, S7 K; Z2 N8 S6 _3 u/ |$ _
to recolor-patch
8 C* i1 `4 Q% F2 o( y set pcolor scale-color sky grain-here 0 max-grain
5 ~& Z- C( u4 D* x uend+ q7 o) L; `' S( d% G4 |1 f' K" H
to setup-turtles# D! i# W D# y; k3 `1 Y
set-default-shape turtles "person"
5 ^5 J c7 _: X/ G9 L5 o/ y crt num-people. E1 p2 [) D" K# G/ u8 v
[ move-to one-of patches
$ E5 n0 ^" _: n. H+ }. p, {7 q0 e set size 1.5 % Q+ e8 ^( ?" m" n
set-initial-turtle-vars-age" s* {7 A4 @! Y3 ?9 t; k
set-initial-turtle-vars-wealth
6 a6 |* E; M% L3 @7 l4 v. B set age random life-expectancy ]
9 W, a: v1 ?( d, t( ` recolor-turtles
4 n) z v- p2 F2 l- Xend
. t+ p( g0 L" z5 P3 o/ {# U' {% G( _ t) C% x+ p' d$ ~$ f
to set-initial-turtle-vars-age
; ^/ M4 _3 f- _2 G5 R let max-wealth max [wealth] of turtles& `8 V6 v; c9 o1 Y% P
: Y+ L( N6 B M! z% {
ifelse (wealth <= max-wealth / 3)& z$ a _- F9 B& g! }
[ set color red
% g% a- D9 ~3 a3 r# _ set age 0
6 |$ f; m. Y0 i0 Y- U2 I! x face one-of neighbors4
6 W7 o _9 L0 v2 N: s set life-expectancy life-expectancy-min +
1 x p8 n3 D: C- b8 L3 ~ random life-expectancy-max 3 Y0 q( z/ B: q8 {: u
set metabolism random 1 + metabolism-low. A% J/ g1 Q4 C" h$ R2 b7 ]$ k1 E
set wealth metabolism + random 30
$ m" H1 g5 L4 W9 y8 Z: O* p set vision 1 + random max-vision! Z3 z7 r$ S8 } s9 w8 R* d6 Q
set wealth wealth + Wealth-inherited-low ]5 M2 a3 u5 M5 V! L% C0 V- X4 X
[ ifelse (wealth <= (max-wealth * 2 / 3))1 b" ? I8 Z1 b# s! |
[ set color yellow
, f! y8 a: j& I( h0 @& S set age 0
7 r! W# W5 M% E" N face one-of neighbors4
3 R' u/ e. H& p0 H7 u# n1 C( W set life-expectancy life-expectancy-min +
3 Y5 ^8 l. B& y* ` random life-expectancy-max + 1" h9 T8 G2 E! w
set metabolism 1 + random metabolism-mid! Y1 `2 s( {+ B- V
set wealth metabolism + random 30' ]9 N' Q# A; C: L, B! ^
set vision 3 + random max-vision9 B! Z. ^( u: B9 J; z6 U2 h7 m
set wealth wealth + Wealth-inherited-mid] p& D" f) G3 W2 C! Z
[ set color green
7 Z) d" C' g4 \# Q; k set age 0
" j |5 S* y% C% H. F3 n; a face one-of neighbors4
& {2 c/ k1 `6 b+ U4 h set life-expectancy life-expectancy-min +' ^+ f3 ^6 ~ d7 ]* p: D% d
random life-expectancy-max + 2
% o2 [. }8 F6 |9 I, [ set metabolism 2 + random metabolism-up. I Q' i3 o# K1 V& R
set wealth metabolism + random 30) N# L4 p; z, g; q
set vision 3 + random max-vision5 g! z& ^! G8 u ], y
set wealth wealth + Wealth-inherited-up ] ]
* g; U6 R% P4 a' j8 j8 O $ ~; p4 {4 a9 r/ x% T5 e! a- q
end) B( Q# E* q- \: ^
to set-initial-turtle-vars-wealth
/ p/ L) L) L' U/ j/ j, T$ C& b# T let max-wealth max [wealth] of turtles/ ^* t q: C y% G9 @7 k- F0 A e
set age 00 D4 }& }% F4 b. X# T
face one-of neighbors4
3 y' Z$ o ~- ~. C set life-expectancy life-expectancy-min +
$ h9 q0 u0 H1 x1 x5 F5 ~ random life-expectancy-max
4 L4 Y5 I& x! N5 L8 ~# k5 U0 o( I set metabolism 1 + random metabolism-up
7 r( z6 J) A/ q( n/ |* J! s set wealth metabolism + random 30
3 Y( c$ ^; F1 n4 `$ a/ \ set vision 1 + random max-vision
$ P0 T( W' X2 a' zend
) e5 ]/ P: Z! W. M) dto redistribution+ o6 ^. T! a% J( o# ]
let max-wealth max [wealth] of turtles
1 o# B1 V0 l' J) l/ Mlet min-wealth min [wealth] of turtles: F" J& g, Z$ ]; m5 S
if (wealth <= max-wealth / 3); e0 R, e8 C5 `
[set wealth wealth + Low-income-protection ]& J$ Q+ A0 [2 C" p: y
end$ l* Y/ Y o: z+ L8 [3 [ D5 [
. d @( k& w% p) M5 V+ J. ?: z
to recolor-turtles
: U9 [3 y1 d3 c! g3 {- J7 C) D let max-wealth max [wealth] of turtles
?# P5 N5 B+ h, g Y2 |" Q ask turtles
0 B8 C! p8 ~+ Z: `: z. z7 ` [ ifelse (wealth <= max-wealth / 3)
* Z/ a' Z: ]! x3 M+ A0 z [ set color red ]/ ~. j" j6 J8 ^0 \+ u' @# O" e
[ ifelse (wealth <= (max-wealth * 2 / 3))/ ~. r% D& k$ D# }) O' |& W, n2 Y% o/ ]6 E
[ set color yellow ]# S5 B1 V. E! L, i/ \+ i
[ set color green ] ] ]" \2 ^* ]/ P [3 u( J0 E
ask turtles [ifelse show-wealth?
( R+ X4 m. e# G# p [ set label wealth ]& K6 B/ B* z' a7 r3 \5 ^
[ set label "" ]]
6 T. @5 x. z2 z& `) w3 d/ B+ Dend
# m' x& m3 P# G; S" t I7 B$ v1 S. v3 T
to go
* K# `/ ?* o" y% K ask turtles% T+ l7 d9 C) j# n
[ turn-towards-grain ]
7 i" z7 [$ |! D' C$ O! e7 | harvest
8 ^' C4 s0 y( [4 `+ h5 B& W! W! @ ask turtles
: [0 V) T5 W5 D0 K( w [ move-eat-age-die ]( R% h5 I' w' R3 D
recolor-turtles+ a/ [1 |8 `6 Y
if ticks mod grain-growth-interval = 0
& X |3 K7 h+ R; d+ `0 m3 ^ [ ask patches [ grow-grain ] ]
! k4 V- _( m2 }5 J: _
" v5 f+ |0 V* W if ticks mod 11 = 0
& u% q/ f% \; g% U2 F" M [ask turtles
9 f( j% @* q$ ]* |- j2 @% O% P: s4 X [ redistribution ]]( r: ` a* A. ^& u1 \. j8 r+ D
if ticks mod 5 = 0% c. u) t( E; M& I. B* S
[ask turtles/ J1 a% W" I3 o% _2 s
[ visions ]]$ S! l5 R1 `4 e. a+ R% y- ?# A
tick4 |, o1 j1 O: V& `, z9 {. G( f
update-plots
% e, J# \; \ G. d" ?end
) ^0 \- u: {4 a1 _$ Hto visions
. t& X7 G+ ^6 H+ R" m; Q8 } set vision vision + 1 * g8 i8 x! k: r4 r0 T& I6 h
end4 d8 m) a; q# G# l- k
6 U' ?% T' a6 k7 W! _/ c" K, @$ X
' m# L' j2 t7 O3 I7 ?% h
6 p0 g1 h$ S3 v9 b
to turn-towards-grain 1 ~3 D* G% z4 z
set heading 0
4 ^6 J% i7 j/ ]; l! |) n! q+ _2 z let best-direction 0
3 j z& M$ |* z9 a let best-amount grain-ahead, r" x6 H! w: P- O S
set heading 90; o- L y! `0 O& P
if (grain-ahead > best-amount)7 O9 t5 A7 T& W
[ set best-direction 90
6 J8 ^8 x7 }, k7 Y set best-amount grain-ahead ]9 Q. E7 k* ]# ^5 j
set heading 180
# @% D1 _; A+ y4 |( W- a5 x( X if (grain-ahead > best-amount)! H: S9 E" Y- v
[ set best-direction 1803 B. k; n2 E% u( u2 z" V2 r7 h
set best-amount grain-ahead ]# M1 Y. i4 W% ]- o3 W9 e
set heading 270
8 _- o5 z* x- j, p+ b* B6 s if (grain-ahead > best-amount)7 R4 l7 z" t$ R S/ U, b, \7 f
[ set best-direction 270$ u2 Z5 T2 W6 z" a' b) d8 P/ P
set best-amount grain-ahead ]- ]# r2 ?& n4 \. x: y
set heading best-direction8 e7 f: L1 I# w% F0 s4 |0 h
end+ O) q- ?+ a8 K+ @9 B
1 F5 D p! H3 Z$ Z1 g% z% |/ n) }; T
to-report grain-ahead 2 V5 d2 C4 ^2 P! b# J0 \, p, d3 c
let total 0
! w7 I# [$ E- r1 \ [1 z& H$ Z let how-far 1) b$ [! b: b* \( f5 f* X
repeat vision
: n: k% b* p0 ]; Q/ v [ set total total + [grain-here] of patch-ahead how-far! k* b- t$ K$ j" U
set how-far how-far + 1 ]
( p) `" W; q9 l% z- d4 B5 | report total* o2 n; u! O: U2 ^8 J1 J: v6 Y
end( W7 X/ c4 [3 J! q& @! e; `1 e
9 v5 X; l g5 w, ^, n# e/ Lto grow-grain + c2 C, r" o: o8 y: N: t3 L# g; A4 M
if (grain-here < max-grain-here)- M# t3 }# @& ~) v; \. q
[ set grain-here grain-here + num-grain-grown; i- e8 ~9 i6 b) h0 [- v7 _
if (grain-here > max-grain-here)
/ z1 r0 G. z9 T% ^3 l' J [ set grain-here max-grain-here ]
/ ^$ u8 x n6 }1 W, u5 E, _2 t recolor-patch ]( B0 \6 c. ?( _6 \
end: b' s- Z1 S( i0 J+ b9 N
to harvest
* d9 m5 B& _ T ask turtles
0 U$ B. o' f2 K2 a) K [ set wealth floor (wealth + (grain-here / (count turtles-here))) ]+ n8 V9 e; n7 z0 H, K' q
ask turtles
' `" F$ l8 d6 b9 @& O6 g [ set grain-here 09 G! L G3 G) M0 I
recolor-patch ]4 f& E! P% x5 I. D& H% i
' v# n- \" d+ j$ T) Iend0 |+ M2 ]$ A) Y7 e
5 t: n% J% T! i7 V8 j. Y* I: I6 L9 p
to move-eat-age-die 7 F w3 v# T# g1 I; p
fd 1
0 R9 F( I* Y6 W0 J& | R set wealth (wealth - metabolism)2 T. J" q6 ?, \1 P; W
set age (age + 1)$ g0 K* ~5 X* f, J' ~ `
if (age >= life-expectancy)& E$ g* Z- O* K" i7 L' `
[ set-initial-turtle-vars-age ]: r0 m* }4 {/ Y0 [- P5 J
if (wealth < 0)1 k( ]: m/ @ l. m
[ set-initial-turtle-vars-wealth ]
* o9 [* M; ^! y) a+ R& P5 ^
' a' N0 x1 U$ D9 k* S0 Send( N+ A2 h5 B7 v- P2 }1 t$ Q6 k& k2 ~
6 G" r7 ~4 ]0 d p% ^) m
% |) S! `) \- J/ Ato setup-plots
5 ^. h$ _9 |0 Q0 d" l+ C set-current-plot "Class Plot"( F) v+ H2 `* t6 ?
set-plot-y-range 0 num-people
5 v. ]: P0 @' e; c4 r* L" w, o( ` set-current-plot "Class Histogram"! p6 J) f: X0 {0 a
set-plot-y-range 0 num-people. ?1 N9 ?: t: x
end
5 b- s: Q* T" V* I) z! @; Q7 E8 R. ~8 N4 H! Z
to update-plots
5 R2 j5 X9 s: o2 c+ n P: J update-class-plot+ ?7 P8 T9 H/ K3 \' S$ Y' e
update-class-histogram
6 y" e5 T! x! L& B update-lorenz-and-gini-plots
* l) D( _2 y1 e3 J5 A: a5 g/ Lend9 }7 ? R2 T( V+ P" {
4 M7 m/ }1 O) e# |to update-class-plot
; [5 }% T. r- k/ O( u, Q# _ set-current-plot "Class Plot"$ E5 Y4 ^5 e' }$ N
set-current-plot-pen "low"
2 H0 e* Z0 h, M4 z# l% D; [) m& c! E plot count turtles with [color = red]- U4 B* R5 M$ ^/ y# O0 }4 ^
set-current-plot-pen "mid"
9 q8 }& n6 `) W6 \ plot count turtles with [color = yellow]
5 ^% S, H0 B6 }2 h3 K. V set-current-plot-pen "up"
+ j- Z8 ], f x% b% Z plot count turtles with [color = green] }; W/ Y8 s. C h' Z2 X6 @ h
end: y& S. P, l* ?/ L( h
' }+ B; I. t9 i
to update-class-histogram
# k9 Z- M; ~2 c/ T. H% {* t set-current-plot "Class Histogram"1 D3 g- r, V `3 _8 F1 j# O
plot-pen-reset
0 B( E- z/ e! X ~; L set-plot-pen-color red
, I5 S3 O L+ Z) ~ B& X& W plot count turtles with [color = red]* ~7 A6 s( `* b1 ?) R& |; m0 y( j
set-plot-pen-color yellow4 k- S+ }1 U4 L. \9 y, b
plot count turtles with [color = yellow]1 v$ o1 a5 m* ^1 N& V$ c* W
set-plot-pen-color green
, }1 Q+ a* Q& O( q plot count turtles with [color = green]8 I4 z6 z+ B6 a2 r5 H9 G6 s
end- n; A5 B v% W4 F8 h5 Q- N
to update-lorenz-and-gini-plots
0 ?1 L& j, k* {8 o set-current-plot "Lorenz Curve"( t# O$ x: k" x% N1 B
clear-plot4 [7 N) b" \# T* |6 a; v
8 _ b: z" z$ @
set-current-plot-pen "equal"
" |8 j9 f ?3 j plot 0: P5 e- H: R$ `5 E. e! J
plot 100
6 o% l q, q- L& ~' ]' ?5 d. m5 m
! e- H/ d- ]* H4 I* f6 ]1 { set-current-plot-pen "lorenz"
. W' w8 t4 `" k0 U; ?4 v" ~ set-plot-pen-interval 100 / num-people6 v% L9 H9 w# g+ P6 E* D
plot 01 `8 k ?9 v! t5 C& P t, Z6 U
0 b w% h; J9 X7 S! A let sorted-wealths sort [wealth] of turtles( \& h4 x9 o6 n1 u
let total-wealth sum sorted-wealths
- p, _* f! ?+ R let wealth-sum-so-far 0+ G s( u2 {" z) r9 }6 e
let index 04 B7 a; X8 f+ L# g8 }) w
let gini-index-reserve 0
1 c! e* R \/ C
- j/ E$ |! a# ?- A- R2 V repeat num-people [5 [- W+ J% s- B, U* [+ O3 r+ I
set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths) g0 _' i/ X0 y7 V
plot (wealth-sum-so-far / total-wealth) * 100* f% ^) H5 u, [5 W7 G6 H t
set index (index + 1)
( M% k" ~8 U$ m# I: \ set gini-index-reserve
% U+ @* s/ {/ n) b+ t. i8 ? gini-index-reserve +
4 P6 F# u+ M+ U5 h( { (index / num-people) -
0 U5 e5 f8 m- ` (wealth-sum-so-far / total-wealth). k8 c9 H, I9 A# m4 ^8 N! ?1 |! X
]
: t% S, t1 q& e* @
* S- a( z2 B# B+ H+ Q5 w2 {: W set-current-plot "Gini-Index v. Time"! A0 e' @' R6 r
plot (gini-index-reserve / num-people) / area-of-equality-triangle
: t+ q. \4 J8 d8 A6 |end
( a c0 A. o6 T) q5 C [6 `to-report area-of-equality-triangle B5 }, P; n6 h( B
report (num-people * (num-people - 1) / 2) / (num-people ^ 2)2 A2 Y: U- n% C' J9 g ~
end |