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6 h: R5 }) `' D) S, R
globals; U6 x, K3 m4 F) q- ^ z) C$ y- X
[7 W* A1 C. r" f
max-grain
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]
" {* ` t) r8 Q$ b$ d0 ~. L! t5 q
- Z6 z. I" I% C& N& c* v$ |3 K# Rpatches-own
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grain-here
) n8 v2 U& a. | max-grain-here
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_3 _ _% \" N& r0 a6 q( |
turtles-own
6 |+ i2 {' r+ a7 |- y[' [' h5 g) ^* j0 v7 l
age $ V3 h& V& |9 S1 d3 B0 f/ J
wealth 6 P" u* \8 M2 U3 m9 ]
life-expectancy ( }( @- A; M. X' `5 L; p' h1 T, s
metabolism
/ d2 S+ z0 w2 K1 W5 ] P- T- I vision
9 k, Q0 I7 d& F% u inherited 3 U8 ]2 O: z, e2 v1 K. C; e* K
]7 ?, F P7 G3 ^
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to setup
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set max-grain 50
' h2 J I! s. u6 y setup-patches* O+ E/ A) ? r
setup-turtles
" }& W, C* e: E5 J1 X) I8 ~) | setup-plots
3 S/ j; S/ R: S- d update-plots2 p- J5 u! G# g. n4 Q2 D/ O$ v6 n
end
# s3 n6 {; u5 l4 a; `1 o% y3 Yto setup-patches* w8 ^+ H: e+ X1 l/ ?8 z3 z7 J
ask patches5 q5 f( K$ f7 R$ \1 b! |8 D
[ set max-grain-here 0
4 [) D/ \8 |: R7 k if (random-float 100.0) <= percent-best-land
2 n* R, A) B9 n7 P [ set max-grain-here max-grain# X% a4 Q6 X Z9 O- y
set grain-here max-grain-here ] ]
7 G* g S6 m5 a5 T* n repeat 57 t; H; m0 m( e9 F$ v; f
[ ask patches with [max-grain-here != 0]
/ i( J/ B9 ]$ f/ G/ l0 P [ set grain-here max-grain-here ]4 O- I. W/ p( v- D. T& C! K9 a
diffuse grain-here 0.5 ]8 v0 g4 \1 D, z
repeat 10+ y' H, ~; u' |& h2 u
[ diffuse grain-here 0.5]
5 j+ p( a$ d$ X' L5 g' Y& u ask patches
4 Y# t! \" ^: V5 G [ set grain-here floor grain-here 1 H z k4 y0 b" H0 q
set max-grain-here grain-here 5 A) I- e1 s( R" r7 @. ]9 Y* Y
recolor-patch ]
' `) B! z; C3 J5 S C$ ^7 ?. vend/ i8 l* ?* G8 q7 s( z9 n' r
to recolor-patch 8 T8 @- [8 C9 `3 }
set pcolor scale-color sky grain-here 0 max-grain" Q# r! U: x! F+ Z x
end
2 V ?1 D! q E0 Sto setup-turtles
( {4 N. c* N4 R0 N set-default-shape turtles "person"
+ X7 t9 y1 Y- c; X% l0 X/ ~ crt num-people2 I& B! b' L7 Q7 Y2 c L7 n& z" Y
[ move-to one-of patches
2 Q) U( c4 {1 B# o# N' ? set size 1.5 5 m9 n" G2 X( J( d/ P, j2 i
set-initial-turtle-vars-age& z+ b }) i) U* ~% C6 r
set-initial-turtle-vars-wealth" P) b2 C% f: N
set age random life-expectancy ]. N( }2 ~: C- @. Z0 j! k- s! L
recolor-turtles$ {7 [; d8 }1 O; b/ D+ O( ]
end
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to set-initial-turtle-vars-age5 F; Y9 B% x2 ~7 q3 q- [
let max-wealth max [wealth] of turtles6 a5 y' @3 G N' ]4 B- `; N
3 W( Y6 x) ^( d" ^' S
ifelse (wealth <= max-wealth / 3)/ w0 e" a7 }; z/ ] c$ f8 h) [3 y
[ set color red
3 N `2 z6 p' ?' q* v+ | set age 0
& a' w$ [6 z& @/ Y7 Z face one-of neighbors4 8 c/ B8 X0 k5 Z' p
set life-expectancy life-expectancy-min +" o7 M" l* f4 k* X* {1 \
random life-expectancy-max / M. w& p) T9 n4 I5 S
set metabolism random 1 + metabolism-low
* s$ v& ?0 M7 [ f. c# c set wealth metabolism + random 30% N+ I9 M7 F0 o# F- t, U
set vision 1 + random max-vision
0 g" S# t4 q( z. R' s9 Z set wealth wealth + Wealth-inherited-low ]
% b0 }) @% R$ z) \7 O) n5 C6 V [ ifelse (wealth <= (max-wealth * 2 / 3))* Q& S& g6 e0 {/ q: e8 I7 F
[ set color yellow 2 z& ^* P# X/ d9 C4 n6 q; q# Z
set age 0
$ P% d4 s# V: q; x) Z3 N! E1 n face one-of neighbors4 . W: e0 o4 ?7 Q" I% O# N" M
set life-expectancy life-expectancy-min +
* Y3 p! y& j6 ~: t4 I c) w random life-expectancy-max + 1( a6 w& R0 u& L* e# g& a
set metabolism 1 + random metabolism-mid
& m6 C( q2 B* E7 }0 g, W set wealth metabolism + random 30
+ k% u; d" w: [% X set vision 3 + random max-vision' j$ a1 U( ^; U
set wealth wealth + Wealth-inherited-mid]' {! t& q8 K! F+ Q R
[ set color green
1 S5 W1 b9 U) S& n6 g set age 0: q, ]/ a, g- I$ ~
face one-of neighbors4 $ \% z# ^3 ]$ {6 m3 P i
set life-expectancy life-expectancy-min +3 Q2 }, Z2 B+ `/ H) e+ S
random life-expectancy-max + 2' H W& K; |+ p/ N% B; o6 ^; Z
set metabolism 2 + random metabolism-up
4 W0 q9 }5 m3 T+ T9 [' J set wealth metabolism + random 30& e# [, A- c) j+ Q. R8 g
set vision 3 + random max-vision
7 I/ K4 O+ h+ c* R+ k9 n set wealth wealth + Wealth-inherited-up ] ] ' w1 x4 T+ O4 V: i* K% _
- K- j1 U7 O- C3 c9 f8 f7 p0 O
end
1 q2 l% X# [$ X+ e* L# Zto set-initial-turtle-vars-wealth! P {4 Z4 Y2 S
let max-wealth max [wealth] of turtles
2 e" a# M7 q i m& w+ d5 N set age 0
: v) U% w4 N' B$ o, l' @+ B+ { face one-of neighbors4
- |( j* Y7 \8 g( L6 ^ set life-expectancy life-expectancy-min +; t8 G( [* s) d+ G! W, d: G
random life-expectancy-max ' w6 |$ ^# i, W* |, X4 I
set metabolism 1 + random metabolism-up8 I( ]' w* ]3 k# W: A
set wealth metabolism + random 30: R" x+ I& ^: U: Y- K
set vision 1 + random max-vision
+ d2 s' H+ j+ I0 ^4 p6 w* zend( ~: O( E# Z, O/ U6 n" u
to redistribution
9 z" {0 i- X. M. Nlet max-wealth max [wealth] of turtles; }+ V% I& U, y1 d4 W( B5 a3 l9 O
let min-wealth min [wealth] of turtles- ^0 p8 a5 m5 q5 E3 l. O
if (wealth <= max-wealth / 3)5 L* |* y0 q% I& m
[set wealth wealth + Low-income-protection ]3 Z3 A0 y2 t/ r7 e& ^* y* K# K0 w2 d) o
end
3 U- T! B. Q: x8 o R5 V& b
, o x, f, W1 h H- z% `) L% y. l Lto recolor-turtles
/ ?& v& f g% z let max-wealth max [wealth] of turtles0 x2 H* b: g8 ~$ E q+ f$ L7 \1 ^
ask turtles# h' [, {9 h. W3 c" D+ t
[ ifelse (wealth <= max-wealth / 3)
, Q" J" }( f4 b0 I4 j$ g' g [ set color red ]% t1 [0 j+ Q$ F0 o* M
[ ifelse (wealth <= (max-wealth * 2 / 3))
# }1 d6 r7 h5 N1 E! | [ set color yellow ]- u1 b& ^+ O3 t$ L" ]
[ set color green ] ] ]
! }3 x3 t+ Y. L* K ask turtles [ifelse show-wealth?
% S% A; a( W" `5 u6 H2 A [ set label wealth ]
+ j# Y8 B0 l& ]' \) R [ set label "" ]]0 c" H! q& G5 p1 G7 S2 v
end1 B' a( Q& P4 P+ R
+ p% U; P0 y6 h4 v E6 X: W! B( xto go2 m T% J" j+ y3 r6 R- F
ask turtles; B# v9 ~$ P# Y) r7 p$ o' K8 |; R
[ turn-towards-grain ] ! n& @9 ^1 k# J. ]& k+ O) r
harvest: m* m4 `, B ], F" J
ask turtles
, G) @+ Q; M" Y& F7 O$ u [ move-eat-age-die ]: Q9 X/ {( ^8 B/ B: x! t
recolor-turtles9 X/ T* ` t9 h6 D0 ]: n" C- ]
if ticks mod grain-growth-interval = 02 a/ G& K2 Z4 w% R5 p
[ ask patches [ grow-grain ] ]" S7 v: @: s& o0 K& @% T/ O
% k% `! s3 b& d8 W$ a+ R$ V if ticks mod 11 = 05 g, h: [% `: B8 n
[ask turtles4 Z* Q5 o9 J5 W# m! O+ D
[ redistribution ]]) x% G) A$ Q7 l' \) I
if ticks mod 5 = 0. e Y7 U3 ?% W; k" ]$ e2 S3 U4 d7 s/ |
[ask turtles+ K7 K6 \, N& m7 n5 i. ?
[ visions ]]/ o9 Y: x9 ]9 V4 x/ I( E
tick5 x$ ]/ [- C# m9 S g
update-plots
: T% u/ E6 ]% E8 I$ Qend
7 U( D! W- E+ Cto visions- Y. x, W2 L- W% c& V& Q# f
set vision vision + 1
8 @2 h/ C2 A9 a- gend
4 A! s/ E+ [# W8 w6 K f. y U |! n8 A$ ?7 C& L0 n) U
d" O" @7 D5 L- v. N% x6 A- m/ U$ H$ e; l% T5 c4 y' x8 c
to turn-towards-grain
3 A( a; k) R" A7 L) X- i$ C. `' j set heading 0$ _, G8 v( x- z0 j5 a% M- L' z# q- e
let best-direction 0; X) ~' v" ], X; N3 y" M2 N$ f
let best-amount grain-ahead* |0 e) s- T: |6 {* ]! P: Q% }6 s
set heading 90
9 S1 ]5 k) o$ @ if (grain-ahead > best-amount)
' f/ M2 N5 ?- w+ f3 n' c [ set best-direction 90" a& P- P! [; X
set best-amount grain-ahead ]. u* Z* z$ r, {
set heading 180$ E+ M( X2 M9 J
if (grain-ahead > best-amount)
g0 h+ W |/ n7 M: { [ set best-direction 180) y, n5 O: E8 N7 O
set best-amount grain-ahead ]
% ~' L2 @. `4 Z( Q# y$ T set heading 270# r+ I: a6 C: @; p, J3 ^8 U
if (grain-ahead > best-amount), J: R3 o) R& d+ I: \& f5 b5 ^) B
[ set best-direction 270. P* H2 D1 D- f; w5 O
set best-amount grain-ahead ]
9 @# r/ H5 p6 b* {5 C/ l5 a set heading best-direction
\0 s/ u8 |. F% L) jend
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2 y) I0 `. a. y* L' A& U! K
to-report grain-ahead 1 G4 h8 a5 g D+ p2 a; ^$ P5 z4 r
let total 0+ d5 v/ R. n( W" V
let how-far 1 V% j+ C, @9 Y( E7 p: \! F% P
repeat vision5 s0 P) G8 D: Y# s; M/ \
[ set total total + [grain-here] of patch-ahead how-far7 ~1 K! o4 }, R: j A4 w$ j) w* W7 G
set how-far how-far + 1 ]' q/ L7 z* p2 [8 [% K& {9 _
report total
- J- y% p. F& p" B1 Bend- u+ ~" m* O$ `7 o
9 T5 t8 E E0 F9 z: d1 h
to grow-grain : T1 g( G" K/ I, j5 i' b
if (grain-here < max-grain-here) s/ B, y' @' I" C. w w: x
[ set grain-here grain-here + num-grain-grown2 u( [, s* S0 x% g0 O
if (grain-here > max-grain-here) / o' b* v# \$ F
[ set grain-here max-grain-here ]# h% @4 {4 L+ B+ N
recolor-patch ]% m& k/ a' B2 ?! Y" y/ d% k6 X6 q
end5 q9 Q$ _/ O/ z) S
to harvest" _; g( J, r9 J; y: i, X& N
ask turtles; a t/ e+ L A$ I
[ set wealth floor (wealth + (grain-here / (count turtles-here))) ]
- b) h8 q8 u z( {* I9 H, L ask turtles5 n6 |+ H5 E9 w2 }7 F
[ set grain-here 04 I0 C9 q5 z1 j3 y1 B+ b
recolor-patch ]9 h E9 F. Q, V3 u' W; [! g
: w7 x+ w" C! L, a0 V* Fend5 v y, M! g; ]# f/ _
* w8 m8 w0 r& hto move-eat-age-die , C" G0 T. M* d* p. @# [5 x2 T- N
fd 1) T7 y: H3 P/ B' V9 c: r
set wealth (wealth - metabolism)' ]3 ]( C |9 k+ } j: i# I! |
set age (age + 1)
4 ]& v9 N7 s) F6 c9 Q if (age >= life-expectancy)- }# |9 T+ R0 z& x% @
[ set-initial-turtle-vars-age ]
, Z9 J: y O- n7 V& @, J7 g if (wealth < 0)% J' A9 r% K/ n! A3 J; A. l! }3 g! N
[ set-initial-turtle-vars-wealth ]' m/ Y0 L) f! D! L3 O) q' r7 J( x
) u( |& v2 x4 `
end$ w' f* c) O" M/ z& c
# J# z7 ^- W" i: m" m! Y; Q C, b" o8 v8 z# r+ ]
to setup-plots
9 h* T1 b+ \; B8 Y2 M9 O# r5 y set-current-plot "Class Plot"2 m: D7 i/ p8 W! u; J$ v8 a5 b: ?
set-plot-y-range 0 num-people: _& H6 _8 f: r# A& H& |
set-current-plot "Class Histogram"
9 R2 `$ B; v y+ V+ S set-plot-y-range 0 num-people
5 t- h) M& W s9 W5 i$ Z0 W: eend
% O# f K& V& k/ \% ]7 ?. k
+ F. l) `) ?4 W' A' j9 Uto update-plots/ Z0 w, v% ^, ?" u9 g% v4 D' | V
update-class-plot1 c+ t$ [7 O8 _' c. K
update-class-histogram" q+ m/ J9 E% {- G& b
update-lorenz-and-gini-plots7 E! \9 q" Z4 \7 A, U. I
end
& L% Y" Y! a; H3 n% ^8 p
* c/ y9 S# I; n5 Z6 pto update-class-plot& }( u9 C( b9 @7 x) t1 h+ b0 G
set-current-plot "Class Plot" H m' r; v7 e6 V% s: V0 n% N
set-current-plot-pen "low"
" h4 u2 T3 b: m0 E% B* V: ^ plot count turtles with [color = red]4 f( E% _! q: Z! }8 `& X7 x
set-current-plot-pen "mid"
2 W" h8 j, D3 E plot count turtles with [color = yellow]
! b4 s7 a- f6 T* a/ u0 A" P' i set-current-plot-pen "up". X, A/ J5 Q0 C
plot count turtles with [color = green]
( ?6 v! n+ T/ @3 b" m. Q/ ]& z Send2 e2 j$ f! h6 [: {# i4 d: V
2 ]; z8 g# V" i4 Kto update-class-histogram
4 ~/ n; I+ T" \' R set-current-plot "Class Histogram"
+ ?. K2 c' o2 Q9 ^8 O6 }( [ plot-pen-reset
+ S8 }3 |% Y1 ]" } set-plot-pen-color red
0 S1 b1 Y& W b- ` plot count turtles with [color = red]
3 s3 C1 g: y+ ^8 V$ C4 G set-plot-pen-color yellow7 Q( W' R; _; r P% k
plot count turtles with [color = yellow]" U# l& d0 w/ v0 c. @( O
set-plot-pen-color green
/ q- T4 [8 k: T' E plot count turtles with [color = green]
/ k9 l8 l' z; |1 X( s: _) ^6 Nend3 c, X" p+ z/ Q: R5 Z$ h
to update-lorenz-and-gini-plots
" D8 Q' \" u& h5 d set-current-plot "Lorenz Curve"
) P, C7 R6 x. |3 n% ^ ?5 e. F2 l clear-plot: n% l! r! i1 A
" Y8 {! h' Z, Q: q+ |+ o( O set-current-plot-pen "equal"
' e$ t) t2 q. F7 J/ U2 t plot 0
; H6 e# b+ w, O2 ]% d plot 1006 v d$ i$ }. X
' Q$ H- V% [( V4 ^; B0 {8 h set-current-plot-pen "lorenz"% _' `) I# F0 G3 z; y3 \9 N3 f& y/ @
set-plot-pen-interval 100 / num-people
/ ~* o0 Y) a0 [ plot 0
2 z$ Q2 [+ z. K) t% g
6 [: h9 n# P+ y( `7 k let sorted-wealths sort [wealth] of turtles
L" N! g* [( n" t$ a! f, X let total-wealth sum sorted-wealths
+ y( Z! ?1 E! O8 s$ X let wealth-sum-so-far 08 h9 K7 p& ]' ~6 {
let index 01 s8 R2 n" L* U' Z
let gini-index-reserve 0
5 v. W D6 t' g$ \$ _+ [4 b/ F& X/ _% Z
% M7 V9 p% Y% G6 g1 L repeat num-people [" l$ i5 W, g3 w- y) g% g7 t
set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)
9 W6 l+ V2 U. C& w; ^ plot (wealth-sum-so-far / total-wealth) * 100. K$ n: [- L6 t5 {9 P! ^
set index (index + 1)( Z- ]7 L8 D" o1 L7 s
set gini-index-reserve, n2 u; T' E6 I9 N0 K7 U8 T
gini-index-reserve +5 L; D* B& o9 u! x4 ?- J5 d5 `' H, G
(index / num-people) -
! P+ d. F; X2 L6 Y8 p (wealth-sum-so-far / total-wealth)
8 N3 u. a8 ]8 Q \7 F ]. r4 K7 S: q4 `) D
# J* R4 R l* s9 o8 B$ g set-current-plot "Gini-Index v. Time"+ i( A; s' G2 S2 n: m
plot (gini-index-reserve / num-people) / area-of-equality-triangle
' S3 J4 U* k( Y3 w; O3 ^1 Z8 Mend. i K: d0 O% c- ~
to-report area-of-equality-triangle2 t1 g+ `: x% x, n# h; R# d
report (num-people * (num-people - 1) / 2) / (num-people ^ 2)
; N* m8 K# r$ X4 r( w* f3 s9 W7 @* pend |