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
" N0 c$ }- N# `8 W6 s; D& V7 L+ Wglobals- A: F1 M; W# _; u0 p
[
( g: w: j ^$ W* y ~7 F" N4 r0 Z max-grain - x0 |/ E* C- p5 J U1 L& J
b$ R: i; f/ r3 |" h]; r& k' z! t; X8 c/ B# e3 E) m
9 z e! R. }9 R% A/ z- Jpatches-own
4 _6 H5 [* M( x t[
* f' b5 j+ r9 y grain-here
- z9 F* F5 T8 d# s& l# P max-grain-here 3 }; r: \9 s) _4 M1 n0 p) \1 b
]* n/ `% f4 N1 b$ }: s
& b; \5 @$ |' m- G j7 c
turtles-own
& X# p. P& {- @" n1 K; J[
; b0 f" m2 f& l2 | age ! V: N# A. @! r+ x' z
wealth ) M* @8 k# C V" W% v& B7 ?: ~) |
life-expectancy % {5 G) x( X! \8 m& {5 ^
metabolism 1 V" R! Q! ~: l
vision
' ^' i. e- m$ K/ N% L) Y inherited
7 D# f6 P$ {. k/ K( L]
: m3 f. b+ [! Y! |, j
& e* y9 y7 _3 n1 g" ^ S5 v9 O9 l" _9 V. ]! |$ G
to setup
. P8 J; h7 {- S( n4 E* A ca
5 j$ S% w7 k; N4 a7 c0 f: e0 ^ A set max-grain 50
% w& O8 s( W8 `$ | setup-patches5 Q) [1 a3 j, m% K, Q: ^
setup-turtles
# r5 g H. r4 i! y, w7 ~7 A1 v setup-plots7 z+ e' u* W( D1 T1 b9 h( d. u c
update-plots. v+ q* f( e8 ?: K! f
end& j5 Y+ Z; W6 W' U1 Y; y8 N
to setup-patches
# j4 Q3 N |4 i7 T/ i7 m2 v ask patches0 t$ d$ T$ w9 S3 V4 p. E# ^4 f
[ set max-grain-here 0, w! s {8 t* T; P8 ]0 V
if (random-float 100.0) <= percent-best-land
! `, ^3 p& F3 t% ? [ set max-grain-here max-grain
' v" |! H) `. L0 e set grain-here max-grain-here ] ]) b. Q. B, ?4 C/ u$ P
repeat 5
+ `, t2 H0 b" N# a* L [ ask patches with [max-grain-here != 0]
2 a' E; s: J. P; R) S1 o8 e$ u4 Z [ set grain-here max-grain-here ]2 f$ c4 ~& F, q: `7 k" F4 D
diffuse grain-here 0.5 ]
# [$ Y/ P6 S/ j+ A repeat 10
# T/ {8 [1 c& y2 D- {1 [ [ diffuse grain-here 0.5] 1 t6 Q: G- ~. B7 P5 v# d, u
ask patches
' F( y8 E9 m% @. w7 l) S [ set grain-here floor grain-here
; s: h8 Z5 e+ e5 ~ set max-grain-here grain-here
8 u% u3 B% ]4 P0 @- l+ I recolor-patch ]
/ A6 U/ w' p. v: k' S# [! hend
3 s/ Z- [, F! q+ mto recolor-patch
, c+ a- r5 j* p i set pcolor scale-color sky grain-here 0 max-grain2 G1 H7 s3 P5 S
end! t5 X; ~7 v. b, }& a; b+ ~3 A
to setup-turtles
3 X+ m6 }5 d; b" E0 F set-default-shape turtles "person"
. U( P* |4 B2 z5 ?8 F7 p crt num-people
`0 m+ S) Y5 l8 z$ u [ move-to one-of patches 9 e5 }/ w, Y' k/ H! y
set size 1.5 # z9 E2 P) g' o0 u0 K& H
set-initial-turtle-vars-age X0 X Y% @7 ^3 G% X- @6 V9 N
set-initial-turtle-vars-wealth
. u0 X1 Z- J# R N. m$ f set age random life-expectancy ]
) g9 r5 R3 ~) l) l8 V recolor-turtles
4 }6 \: y3 Y4 bend
1 L/ g2 Z0 \! R, U2 \2 a o6 D& ^5 l
to set-initial-turtle-vars-age
, M5 w( `$ X2 Z8 M, h4 r0 c9 i let max-wealth max [wealth] of turtles
& k& ?( L% L! [, N: ^/ p
% a% X/ ^# n' {( J: P9 q* O ifelse (wealth <= max-wealth / 3)
; v7 E) b! Q2 x9 O [ set color red w y. P1 U+ V' }9 U
set age 0
2 G. V( M8 U3 X5 T face one-of neighbors4
5 ?5 W- q6 y, d) [5 u0 d; V) ^ set life-expectancy life-expectancy-min + {8 H9 y- R( W$ S
random life-expectancy-max
! z T7 x; S$ ^$ s1 n* ?$ s) Q4 o set metabolism random 1 + metabolism-low( w' t/ ~' N" u
set wealth metabolism + random 30! D& P C7 |; W9 c( ]
set vision 1 + random max-vision
4 [$ T9 h, `" \% p' }1 R2 m9 A6 `' x8 n set wealth wealth + Wealth-inherited-low ]5 E+ J' c8 k* S$ |, p& J: V
[ ifelse (wealth <= (max-wealth * 2 / 3)), R* o! ~7 X! j4 K4 J
[ set color yellow
. v- B2 M; d2 I, C" ^ set age 03 F4 b* I; s% C. S! j& l2 _
face one-of neighbors4
$ [0 G; r& \9 s' C- Y set life-expectancy life-expectancy-min +
& O9 g( ^/ Z+ w- ~ random life-expectancy-max + 1
/ Q+ w9 w. K; f" K, g$ a/ v9 ?. y set metabolism 1 + random metabolism-mid% Q& ~# `# }5 C! q, S' V0 u+ f+ C
set wealth metabolism + random 306 V/ w8 J( A: _/ i k/ a
set vision 3 + random max-vision
4 }. ]& b9 M9 ^2 V7 I set wealth wealth + Wealth-inherited-mid]" S' g+ R. u6 T' n) O5 W4 J; D% b
[ set color green ' N. w' T. q' ]8 E: p
set age 0. ~* ~$ A/ u: |: Q
face one-of neighbors4
) k: f) z7 z/ m0 y: }6 f3 [, S% f set life-expectancy life-expectancy-min +
, r( t6 i% g/ {8 z random life-expectancy-max + 2
; W5 U+ j+ k5 ]5 A set metabolism 2 + random metabolism-up( `: G1 Y6 E5 s1 G1 L
set wealth metabolism + random 303 j& e) f ~; Y5 p: i
set vision 3 + random max-vision
7 }: h8 Y" d4 m5 @: P+ i: @ set wealth wealth + Wealth-inherited-up ] ]
7 z! G: x2 S; \* `3 B
4 t; v @5 \1 R; `! j$ Xend
* v' ?' U6 S7 ~. ]/ ]) wto set-initial-turtle-vars-wealth+ V9 }0 Y9 j2 \$ G; f9 c0 C: `
let max-wealth max [wealth] of turtles
" {- O# [& |0 ^2 c8 h& I set age 0
7 B# j J% h2 O% l+ i, R face one-of neighbors4 2 }5 w* T# Q- C7 _/ o; B6 Z( x, W
set life-expectancy life-expectancy-min +
' V0 W# B/ `9 U, Z; u random life-expectancy-max ; u' E- G) H7 s
set metabolism 1 + random metabolism-up
$ B: W9 z7 f- N& p7 x5 n' |3 p set wealth metabolism + random 30
' r% `2 m* R9 s5 A; q% B6 k1 |; N! p set vision 1 + random max-vision
: g7 h. t# N! m/ ]2 ^end
. h! [& C2 y% V5 Wto redistribution
, C! H" J! q0 O) Xlet max-wealth max [wealth] of turtles
: w# Z" }8 ^6 E Olet min-wealth min [wealth] of turtles
, \6 f* d, I* @) q4 Aif (wealth <= max-wealth / 3)
* S; k- X/ M# P2 _ H [set wealth wealth + Low-income-protection ] w9 e% e0 W9 N/ Z3 M4 X! ~/ D7 a
end1 a- d3 C1 Y/ O) K# R( \
, W+ _+ k$ u5 ?to recolor-turtles7 a% o: r* D* E. Z: s
let max-wealth max [wealth] of turtles
; ?- L( C3 F c* s4 k3 V ask turtles0 y9 T1 E/ u" _( j5 `
[ ifelse (wealth <= max-wealth / 3)
8 k" [6 h) T( L+ `$ w6 j. | [ set color red ]
. P! ~( M* N0 e5 F3 D f [ ifelse (wealth <= (max-wealth * 2 / 3))5 g) g* }- G3 }6 C+ I
[ set color yellow ]
) {7 E2 O r0 {. c* \ [ set color green ] ] ]
# y( {3 J. F: g7 g6 u9 n+ b ask turtles [ifelse show-wealth?! }7 d* f% Y( A% L
[ set label wealth ]
4 s) S9 b2 E/ Q# Y/ i; D, g3 v; ] [ set label "" ]]
# a+ F0 B) ^% k% V l* }7 fend
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to go- ^6 k# W6 i: f, Y- s7 S! ], O
ask turtles U: y1 h {3 e! U+ P' K, i
[ turn-towards-grain ] " P, T6 S2 G4 X7 c
harvest
. `" F. [2 L) U5 \ ask turtles+ _! C! d j, V) g
[ move-eat-age-die ]
7 x7 @& t# h6 b9 I8 c& `7 E recolor-turtles. ~" P% }4 f& @+ Q# c) K1 i" g
if ticks mod grain-growth-interval = 0
) u' j( n# b" h+ ?2 T6 } [ ask patches [ grow-grain ] ]6 O, U: c2 ]8 u" ^7 C
1 _4 A2 h$ t/ ^% R9 } if ticks mod 11 = 0" h+ N1 w. G1 \$ ?# ^, s Q; n% Y
[ask turtles
' J: ]+ Q) J- {7 J0 V [ redistribution ]]
2 Z% u+ ~: x( B2 n# W* F if ticks mod 5 = 0
) D7 j( K' Z) H& r6 N. T; L [ask turtles( x% _3 \+ z9 y2 Y7 a Z' E5 X, E. T! d
[ visions ]]
8 A6 K U, i5 ?% q! _# C tick9 H8 h9 I3 T9 ?+ x7 q) t/ M* X W& V* h; Q
update-plots
9 z- A' f& Z2 m8 _8 Oend
% E+ R+ x1 l0 k3 ~2 g% Yto visions! Z$ j3 F( {8 i* t
set vision vision + 1
, T3 _( V8 x( }: ]end8 J/ f ^6 D1 u; a8 I( B) D+ }0 Q3 |
* r! n% c* c1 k% y9 |2 \( b! n0 h+ L, W% Q1 W- l( r. ~
, k5 B6 P4 A, Y2 M0 tto turn-towards-grain % Z) ?1 g6 \6 D3 a/ n. P" e: Q
set heading 0% q0 w' K/ J4 L! [
let best-direction 02 W9 K2 N: L ^! F. c. M/ ?& r9 S
let best-amount grain-ahead
# ?9 Y2 f% r5 X0 i) n set heading 90
8 G8 w# e/ @ f3 b: s/ r+ W if (grain-ahead > best-amount). B' f! L% S& [: B4 m$ Z
[ set best-direction 90
% w8 U- s0 S3 C4 t b6 O set best-amount grain-ahead ]
! @- n8 I0 t0 C9 X1 v- b set heading 1807 `2 `4 f7 p1 Z: g8 O/ Q
if (grain-ahead > best-amount)! T, h% Q& A" U3 n! i e; s7 ~! p
[ set best-direction 180
" f0 {0 |; r8 L! H, A set best-amount grain-ahead ]
) P: D U6 C2 N) f% [ set heading 270) e/ A1 M8 `1 I7 {
if (grain-ahead > best-amount)
3 \" ~7 Y6 c; s! I- v3 l [ set best-direction 2708 V7 C m0 E' X0 H0 B
set best-amount grain-ahead ]
G4 [# K! c5 d: G7 u set heading best-direction9 ~8 d" n( G& |9 A1 \" b+ I4 T
end& \' k$ `. T% m
5 [* ~) o' X9 ^9 J- h
0 ?( M3 L& ]5 A* N+ J1 t4 c% o
to-report grain-ahead
/ T+ I5 P% Z' @) L- a+ r let total 08 ]. g3 a. k0 S
let how-far 10 t" D3 B9 b; \2 z$ ^, u9 b) A2 `
repeat vision
5 W8 {6 s% G* N* O, `" | [ set total total + [grain-here] of patch-ahead how-far7 z# A' U, `) k+ S9 N
set how-far how-far + 1 ]6 q" [5 `$ Q- J a6 C$ f2 y+ u
report total
8 |+ h% R$ d1 y. @' u. I4 m4 Kend j( Y/ i' T" m, b, O
/ ~, {- Q# B' X' V l7 [to grow-grain / B% |; T9 _$ [; V& w1 q3 O
if (grain-here < max-grain-here)
; m4 b+ t: J1 _* m. B) {- q [ set grain-here grain-here + num-grain-grown
# J, ]3 Y' j7 r' W4 m% n! H$ j if (grain-here > max-grain-here) 2 G+ n5 i @+ |5 G# ?' j! J
[ set grain-here max-grain-here ]5 z7 T& a8 D7 b' r7 R
recolor-patch ]
+ W% ]( z' e5 A! bend) [7 u2 s& H; E' S; K! L
to harvest! m5 c5 J+ Y' H" u/ l
ask turtles
% Y/ w; f$ ] I" q) ] [ set wealth floor (wealth + (grain-here / (count turtles-here))) ]0 b* }& K5 _! u+ B/ B5 N
ask turtles6 a. _* u8 X% ?: ^8 q
[ set grain-here 08 l4 D# l u8 `6 T3 A$ T
recolor-patch ]
4 U9 S( r/ X l+ r8 \- [+ o
) v' G5 p9 j% hend ?" P( B( w; _: G2 \$ {. R
% G- {( D" ^6 g5 g n, }6 {/ J. Eto move-eat-age-die
g# a; y! g. y0 T fd 13 q6 D' S2 r1 d# |, v5 `
set wealth (wealth - metabolism)* ?7 H$ k& G4 T0 p' x' b
set age (age + 1)
' p6 H. x) p6 a; K2 D if (age >= life-expectancy)
2 E, e9 b9 y p8 \5 G [ set-initial-turtle-vars-age ]1 X- M( I, r, k" C; V( m
if (wealth < 0)
6 }7 ~2 N# X3 w8 r [ set-initial-turtle-vars-wealth ]$ ~3 z* Z# H( V: K c) O3 y* n/ b
; x4 e% ~. e! ~7 K4 P- {2 H
end9 q! Z" F' q% J' Y8 \* E2 d* M
% G+ ^: @; e6 ]3 I' `9 U% h7 ^; ~
& M& k' a! _* h9 H0 F
to setup-plots+ P3 t. O0 I5 P/ z6 e1 {
set-current-plot "Class Plot"
; a2 }& C# q5 ^8 Z set-plot-y-range 0 num-people
3 @7 |$ K B8 U2 d set-current-plot "Class Histogram"3 A" s0 n2 b3 T" }, [: E2 V0 [# S$ V
set-plot-y-range 0 num-people
5 g0 L9 b) q& ]( r& uend7 X) r0 _& |7 L+ C7 }
7 ]0 n L( q) e0 B; \to update-plots; D) i# A8 n: z1 ?
update-class-plot
8 L0 H# \1 R% Y5 T# E1 Y. M9 c update-class-histogram; x' `3 I( A8 L$ m& L
update-lorenz-and-gini-plots, k3 I5 [ }; H* ~# S( R, S# @/ e) |
end. Q2 t" D, u- b- v
6 p/ q$ l( M7 x$ r$ \2 z9 Mto update-class-plot
* B! G% A" Z0 n, ? set-current-plot "Class Plot"8 X' p! L1 _$ N6 k
set-current-plot-pen "low"
. h8 z% g+ W8 Y r plot count turtles with [color = red]
; ? }1 Y( q7 t) o set-current-plot-pen "mid"
7 D. T. L4 C; P$ }5 Q x( ^ plot count turtles with [color = yellow]+ d( ?+ B2 H' ^2 z" E- X; s
set-current-plot-pen "up"
% ~ O5 S0 z* o: u5 | plot count turtles with [color = green]
/ e6 H' P! m, ^3 H9 |8 V2 Bend' ~0 \" [/ S7 `$ v2 U, \ t
. r& H; f5 ]# N' w7 {* c
to update-class-histogram
" Y5 I4 T2 q* |( P0 L' R set-current-plot "Class Histogram"' Y. ^: w- K- u0 }( [
plot-pen-reset+ s+ G0 K1 ~$ [/ }- [3 G; W! x
set-plot-pen-color red) ?& C1 y3 u; E) p
plot count turtles with [color = red]
; V v7 c* M' L9 ~/ ?% F, M set-plot-pen-color yellow& b9 ^. Q- R* z
plot count turtles with [color = yellow]& T6 G _0 r9 m4 M8 y* m; H
set-plot-pen-color green! ~4 I+ ]- m: y. M* T5 \
plot count turtles with [color = green]( |; w- R7 O0 ?
end
3 C) X" U8 R+ c- i9 D0 d kto update-lorenz-and-gini-plots& r; I4 p N/ T, z
set-current-plot "Lorenz Curve"
1 p! K* K4 I0 {! s, y# Q5 N. g) `3 P- B clear-plot
# _1 V r* z7 K) l! j1 F. a( n8 S
set-current-plot-pen "equal"7 b9 Q7 K2 W5 n+ g3 b
plot 0
, T4 a2 y9 e& V3 q/ f2 I" B- | plot 1006 t2 T" I7 w7 ], H7 w
* q7 l$ }7 J3 s6 E# H
set-current-plot-pen "lorenz"
$ n E2 P: Q9 z P/ q set-plot-pen-interval 100 / num-people
: x- T& l6 a% |4 D! Z/ i* q6 E+ E/ l# p plot 0# E+ E& Z X; }2 u/ Z/ [
; q8 H% ~; \3 {
let sorted-wealths sort [wealth] of turtles
' i, a* Q4 g! A# M1 f% r5 {8 e* l% \ let total-wealth sum sorted-wealths+ x* n9 [3 ^0 n8 A
let wealth-sum-so-far 0% m: p9 @! N* N+ e
let index 03 W( m5 D# n g9 D) {
let gini-index-reserve 04 T; H7 P$ u6 J! d: C
( Q1 i. C j# ]$ ^9 y5 ` repeat num-people [% G% S8 H6 w3 d, w0 k
set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)7 A" }1 [/ K: T( @- X
plot (wealth-sum-so-far / total-wealth) * 100
' D% t2 K$ }4 J! u4 h# T set index (index + 1)
3 p/ v+ D- c) i5 u2 z set gini-index-reserve
8 ^: X& |1 \4 ^5 z- i$ O5 A) g8 z gini-index-reserve +
9 j6 K f; ]( p7 h7 h' ^( Y (index / num-people) -6 v$ m8 S0 X0 L5 q5 n, D
(wealth-sum-so-far / total-wealth)
$ S- ?- t! @7 _1 n! ^, p) p* ?) [' z0 q ]
: O( \! l' u( ^8 ?" {, V0 S
& V4 j' R# |* N* J set-current-plot "Gini-Index v. Time"
5 ^5 t1 t2 i/ u3 g plot (gini-index-reserve / num-people) / area-of-equality-triangle
5 r& i2 [* }2 e: b2 |0 \end9 f( q7 ]1 U7 p' j9 S! G w
to-report area-of-equality-triangle
" o( s. ?$ v0 K ^2 m report (num-people * (num-people - 1) / 2) / (num-people ^ 2)
6 y% B. g# U$ M+ u) {end |