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7 [, j/ |; c P c$ l
globals2 k7 m' D; w3 R, Z! I7 V7 B
[
3 e8 N$ s( l- t8 `5 Z: Y' v max-grain
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patches-own1 ~; \2 p, @2 o( s) N1 A0 n, M( y
[
3 C; Z$ a6 v3 C* {; a grain-here 0 c$ K9 H u( ? ~
max-grain-here
7 _" }2 q, [8 f: F9 c]( v5 D( w I$ \# x
+ Q J& c) @4 eturtles-own. G4 O! P2 }9 `0 f. {: A8 M
[ N7 \7 X: {0 J' q) c
age 6 B% u, K2 y. c* D$ |
wealth 1 j$ ^% | A3 q6 c
life-expectancy # p/ V6 W$ i$ U, w: t. M- M
metabolism 9 {+ i" _8 F/ s
vision
. }/ {' n8 {" Q3 I" M inherited # B& O( \: r9 t/ @7 `
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3 k& C8 @5 X8 b* f K
$ `5 S; v6 j ato setup
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set max-grain 502 \" |" _, c2 e3 n0 V. |" @
setup-patches
1 ~1 i! t- M$ r' F& ]- \ setup-turtles
' ?! W1 g$ L5 ?. \2 F5 K: J" ]0 c setup-plots2 o6 v. L6 y/ l4 t. z
update-plots
4 r, v+ O1 `) \& [end" p. c/ R: m+ P" m4 T5 M) d6 a4 S
to setup-patches
, K( d# _; M$ B$ K/ [ ask patches
1 i$ \& M3 b" r [ set max-grain-here 0# m! ?; Y0 F' Z5 ?5 I
if (random-float 100.0) <= percent-best-land
2 q: V! j4 o \% Y6 u- a/ t [ set max-grain-here max-grain
5 \7 L, ]* e( S1 c9 K9 k- s# B5 V set grain-here max-grain-here ] ]' r8 x" p" C1 G+ V! f) v% A
repeat 5
! v# Z) p0 _1 X. x |$ X [ ask patches with [max-grain-here != 0]4 s! o# c7 ~5 T' a8 ~# `
[ set grain-here max-grain-here ]
2 P* _) \$ |* X7 i( Q+ S X- L- [6 W0 w diffuse grain-here 0.5 ]. K5 d7 x" X d# u! u- V& P' K
repeat 10' q* b" I2 H+ {9 r$ `
[ diffuse grain-here 0.5]
1 T2 u% G2 u& K& r$ P2 o6 Q ask patches% K/ U& P! @. Q$ V+ T0 k9 t/ w2 m0 R
[ set grain-here floor grain-here 8 C! [/ m0 ^) Z/ m o7 F5 Y
set max-grain-here grain-here
( I" X4 Q. Q9 l+ G& ~" ? recolor-patch ]
- V2 T; I4 V# b6 O. xend
3 @/ B- `% l* }, k' p; l2 Uto recolor-patch ' W! w+ ~; w5 A8 Y3 e$ ~
set pcolor scale-color sky grain-here 0 max-grain
, z. p! G2 R* g1 G3 K3 O* ~end
2 a4 I2 ?2 U& ^+ Bto setup-turtles
5 v. A! k1 s! [( p set-default-shape turtles "person"( X0 G3 I" E( r6 Z: ]. _: ^
crt num-people
1 \) }8 K2 G5 y) a4 t [ move-to one-of patches % l( c# U4 @9 g! J' w
set size 1.5 & l1 I2 O( Q* e' w3 r# B" D0 ?
set-initial-turtle-vars-age e0 V/ {$ T. ]7 ]! s
set-initial-turtle-vars-wealth
$ O# b5 \ B3 B+ x! U/ H set age random life-expectancy ] D# u, x+ Q0 Z
recolor-turtles% L# {3 {, u4 O: W( C8 Y+ ?
end8 S# C/ P' J+ J( O" t' H
L2 G9 g$ K5 ito set-initial-turtle-vars-age
8 I. s1 b h, u3 _+ w let max-wealth max [wealth] of turtles+ E$ l8 ^3 O$ k' V
8 N8 Q4 x, ^! W- ]- H) S ifelse (wealth <= max-wealth / 3)
- ^2 J4 C' O, t$ l7 E# O# ? [ set color red & Y8 K f% D+ j; A: I8 N
set age 0
0 i! G6 L. z2 G+ S' ? face one-of neighbors4
" o" k4 q2 \2 @1 J) l set life-expectancy life-expectancy-min +3 i2 K9 \) S. S$ g9 f! d/ }
random life-expectancy-max
- a% z5 q; `2 u set metabolism random 1 + metabolism-low. W, q4 H* s4 _: K9 ^
set wealth metabolism + random 308 F5 y+ D+ `( G/ x- a2 M5 x
set vision 1 + random max-vision7 l" e. A% l6 n% z) i- w' m
set wealth wealth + Wealth-inherited-low ]+ e G6 l3 ]% N2 t
[ ifelse (wealth <= (max-wealth * 2 / 3))
/ Z* F- T' G5 N9 P, l P [ set color yellow
+ @- q3 `$ Y+ @3 k4 ]1 D- [ set age 0" t% y2 n' b2 c8 t9 d: h
face one-of neighbors4
! X1 T9 C0 e# Y7 O0 o3 t set life-expectancy life-expectancy-min +* C4 U' X, U, ]/ p8 M, U# b% Z
random life-expectancy-max + 1
0 _0 G6 H: {- L: R7 }9 S% C" W( O set metabolism 1 + random metabolism-mid) ^" P, i4 c# h& |* E+ g
set wealth metabolism + random 30' N @# \6 [* `7 x! o
set vision 3 + random max-vision! T8 B/ r6 L0 |) C: T
set wealth wealth + Wealth-inherited-mid]
1 X3 k p3 k# x% T* `2 l [ set color green
M6 Q! ^# z! g1 ^5 p3 _ set age 0
) Q3 y- k6 f( }8 Y+ {- T face one-of neighbors4 & j- ]7 m( N* Y; c
set life-expectancy life-expectancy-min +6 v x0 A! i# `4 J4 u' C. p D, Q
random life-expectancy-max + 2
, M" i, i9 @ `5 x/ ^) g8 a set metabolism 2 + random metabolism-up ^7 k7 I( a0 T. b4 x5 g4 M
set wealth metabolism + random 30* R$ y9 f" F1 n' _
set vision 3 + random max-vision) U- k& @, p1 k P- g) W+ C3 f
set wealth wealth + Wealth-inherited-up ] ]
* z* _$ E7 v) X4 I0 r/ j1 [
4 \# q5 ?5 B# R. W% Jend7 h7 U) z7 {: ~# M7 I
to set-initial-turtle-vars-wealth s3 p, Y, s1 ]6 C( _/ Y
let max-wealth max [wealth] of turtles
" e! ]+ e4 Y9 f0 w0 q) L. P% [" s set age 0
5 f1 Q. z7 b/ v face one-of neighbors4 : l8 O( L+ q5 G! u/ O; d4 g: w2 u
set life-expectancy life-expectancy-min +3 a5 p# a( c5 u& B2 a
random life-expectancy-max
; B/ o* z1 {: I set metabolism 1 + random metabolism-up
9 G L! n7 s" H+ D- c set wealth metabolism + random 30
$ s7 ]* c- i: c set vision 1 + random max-vision
9 e, b$ z- x+ |' C3 Q, A3 lend% T2 s4 ?6 \0 y0 {) s& x( R- ^
to redistribution. e- @1 a# t4 h u8 U' s0 ]
let max-wealth max [wealth] of turtles9 S% V, H3 ^7 H$ d
let min-wealth min [wealth] of turtles+ W5 }9 Z4 {% L5 j
if (wealth <= max-wealth / 3)
5 f9 v' G5 L) l' l- S [set wealth wealth + Low-income-protection ]
8 Z- P8 X8 e0 L; a9 k( i( k: send. k$ W4 r" U7 |: q8 i* i
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to recolor-turtles
. M/ ], ~ I% W1 h* ?& J8 |; R! @6 e( Y# o let max-wealth max [wealth] of turtles* k& |% {: C% e, F
ask turtles! p' m' e( e+ H$ K/ r3 t: ]
[ ifelse (wealth <= max-wealth / 3)
# E" J5 t3 x9 S4 C/ @0 ^3 Q! R [ set color red ]* L, B( [, ]- H- U4 p4 P" r6 H
[ ifelse (wealth <= (max-wealth * 2 / 3))$ R/ ?7 P- c0 x/ N7 R5 E5 M* q
[ set color yellow ], a! U& R2 m: o$ B A
[ set color green ] ] ]; |' ? n$ @* F0 b+ T
ask turtles [ifelse show-wealth?7 D h3 m/ S2 D, i2 V; |; t
[ set label wealth ]
7 B# ^, x4 m) R# O) L [ set label "" ]]! w( e: L8 y4 w1 u5 t, R! W
end4 p/ x. a A" Y. Y$ [, F
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to go
$ H* d5 }; {* ?8 P9 w ask turtles$ d5 G9 j e, R8 E% t! R
[ turn-towards-grain ]
) X4 R m7 n0 o/ ?5 u A; @ c harvest5 N. l! M' @. {4 f6 S- i
ask turtles8 |3 U O! a; D; {0 m
[ move-eat-age-die ]
, x: g% S6 G7 B; W1 O4 C recolor-turtles- p: R) C) j s. [8 \& P
if ticks mod grain-growth-interval = 0
; p, A9 S4 ^- K8 ` | [ ask patches [ grow-grain ] ]
7 N/ o2 j6 e$ ?( `1 B+ V+ f, [ - c& B. A" e; s' A+ t
if ticks mod 11 = 0
; J1 @$ O$ c1 ` P Z! R5 @ [ask turtles
) P( E* Q+ Z m" _# u6 N0 I [ redistribution ]]6 R$ V- `# _ X0 }: q
if ticks mod 5 = 0
, o$ ]8 o& [9 ?; J; C9 b [ask turtles+ y% o5 [" j8 {6 p% ]
[ visions ]]+ G3 k; o; J& t0 @, S: u* C
tick& [+ [! x n8 F5 v e
update-plots( z3 L9 l4 N6 Y7 P
end
* A$ _% M! I d# }: s$ Kto visions
5 w7 o8 _6 y+ t6 p( O# M2 j5 w set vision vision + 1 / f# z6 o/ W* `8 D9 m6 T% {& x
end
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: ^; H& q- y6 i3 M6 O5 Z5 dto turn-towards-grain : d6 ]7 Y+ u3 L: [
set heading 00 o" W$ p- g$ P5 C* U8 z* X, a- p6 P- d
let best-direction 0
! S' _3 m, f$ a/ K5 ? let best-amount grain-ahead
# X( i- D" ^; E, y, ^/ Y set heading 90
4 Y9 l- a+ x; |+ r& ]) z if (grain-ahead > best-amount)
6 y$ f; W$ [' \7 U2 A$ ` B5 o [ set best-direction 90" w, d0 Q) ]1 W/ t% i' `+ y( e# k
set best-amount grain-ahead ]& i4 ~' E- ]3 h4 L5 C
set heading 180% Q" Z5 s6 q' o: r3 W# d
if (grain-ahead > best-amount)
+ e% y# s" T/ | [ set best-direction 1807 u7 z( g9 k$ M5 u# L3 |
set best-amount grain-ahead ]6 s0 t& U3 ]3 W' c) n: }
set heading 270 I, u2 h5 C- A9 J" I
if (grain-ahead > best-amount)
: m. x3 f B2 L" U [ set best-direction 270
* T: q; s( m: l4 `: n9 c set best-amount grain-ahead ]/ H- A# t1 s% M1 a% N/ J2 @4 ^
set heading best-direction
% G: X% U* V: A' ^1 Y. nend
9 q1 S5 p' N* ^; I, }) A- f1 d8 _" z# U5 g% O
0 C3 |4 |' y. M/ v, Tto-report grain-ahead 3 ]$ J* k( l) Q ^7 Q
let total 0
( L/ b- [# J# P) x* }9 A. ]( \ let how-far 1
: ?! @- N+ ^9 p. u4 F: @ repeat vision& x5 I: p. a" i4 d8 c& F- N8 j
[ set total total + [grain-here] of patch-ahead how-far
+ z6 J% @+ m! b% a/ Z2 o set how-far how-far + 1 ]
" n( C6 B8 R! [4 J0 p7 E0 M report total
8 b. u5 E/ K- X9 jend
7 g1 ?" L# D9 n, F0 S0 p( A6 [3 d! D* I3 h' v K6 z$ q7 S
to grow-grain
6 u; s9 _! b) B0 Q. c if (grain-here < max-grain-here) Y/ N1 l" o$ c4 m
[ set grain-here grain-here + num-grain-grown, ?+ Y- D- J2 f2 n) Y6 U5 L
if (grain-here > max-grain-here) 5 e5 X5 A# z0 z+ O
[ set grain-here max-grain-here ]
3 S; a" `, L: p- a; G; M/ ?. H- A recolor-patch ]
+ g& z$ d4 D4 ^% I+ E8 T! I% Send2 S& e/ m0 G# _/ b$ V, }
to harvest% y; P* w/ n# l& i
ask turtles& K5 O1 ?& a" _
[ set wealth floor (wealth + (grain-here / (count turtles-here))) ]
2 |$ ]8 r" h8 C n! \+ J ask turtles0 O" U! U( D( k1 x8 P) _, L* [) _
[ set grain-here 0/ P; x6 W- K9 u( T% L* }- v2 C5 ~) B
recolor-patch ]& c$ f. t! }% B. W/ u
# U, j* ?$ j* k! Hend
* ^0 p" F% b3 Y
4 K$ V( q/ ?+ S' Y% B3 c" [; Rto move-eat-age-die
0 h I) ~9 h2 F fd 1
8 C c) v6 l0 c7 s# ~- y/ r set wealth (wealth - metabolism)2 E8 J; J% p" E1 o4 S) I
set age (age + 1), ^/ [ d- N& E; o7 @3 |( X+ _ P
if (age >= life-expectancy) `; ?; _( i7 k* E5 Y# U3 b
[ set-initial-turtle-vars-age ]
5 @0 |8 t, m, m5 I. H if (wealth < 0)
4 W" ^2 A1 y, E4 ?/ Z3 A/ C [ set-initial-turtle-vars-wealth ]+ \' P/ g* s6 P8 C7 d! W
5 g |1 g. k2 G4 k: v: Q! eend3 m3 n- w. R% h+ f4 G f2 @# |
, _, {4 r* D- i# E: O, h* z
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to setup-plots
9 [/ ^ ^# B5 V6 h7 W; C set-current-plot "Class Plot"$ r3 A" I% {/ [1 A* Y
set-plot-y-range 0 num-people
; M+ |/ l1 t _* v2 w set-current-plot "Class Histogram"- [5 |. h' g. O% S* P3 {
set-plot-y-range 0 num-people- p! k4 a) m" F8 [& ?
end
8 C+ F0 D! }+ N( c" ?9 F# {2 ~2 U9 S$ C6 z, H
to update-plots
O1 x6 C8 V7 `( D+ r update-class-plot
- B* I7 k5 k. l7 t update-class-histogram
" n8 ?9 {+ Q. @, c9 S% m update-lorenz-and-gini-plots
$ S9 L+ A1 t0 y1 A; Wend
( Z( a `* _) h* m: `8 j8 |( r; O8 k$ F' ^% a; w3 H: _/ z8 Z6 m8 x
to update-class-plot
" H7 Y$ g& o( g+ Q set-current-plot "Class Plot"
7 m. x: b& s& E) L! p, ?+ F set-current-plot-pen "low"
( `8 m K1 c' D B4 L plot count turtles with [color = red]
. u7 l `$ |1 S' \: F+ B" H set-current-plot-pen "mid"" t" o+ q7 y9 b0 x2 Q
plot count turtles with [color = yellow]
, N# j1 C, C- F' x- } set-current-plot-pen "up"
7 ?" i; g! t) U3 m7 I h plot count turtles with [color = green]
2 y. i7 K6 B0 Q2 oend
* J* F% j( t: p- t( g5 F0 U' e! N2 y2 \& W7 C; O
to update-class-histogram
, T0 ?5 K6 X! [# L" L set-current-plot "Class Histogram"
& m: [3 z4 E9 E" Q plot-pen-reset# k1 D2 G! k$ q0 Q! I
set-plot-pen-color red
6 Q. f2 ?: t: N3 Y: C plot count turtles with [color = red]
2 ^/ t5 p C8 e5 d. \6 e" U$ m% d set-plot-pen-color yellow& f- d9 B+ {* d( Z- t
plot count turtles with [color = yellow], X& p! S8 R# }- c) D% ^
set-plot-pen-color green* \0 T n% D6 X
plot count turtles with [color = green]4 @4 j8 @1 ~; r
end7 e- ^+ N# R% w8 [, b* f
to update-lorenz-and-gini-plots
_" s8 E0 h( D set-current-plot "Lorenz Curve"
1 J4 s1 l7 t& j* L0 |8 q. d2 a1 e clear-plot- ]% t9 g) P* o; v
. ]: R: y. M2 f$ {: d set-current-plot-pen "equal"" p$ H& Q3 [6 V$ ]
plot 0' K4 l8 m% \4 g1 {+ m* x, B
plot 100
" i+ h$ O; S3 z8 N/ k; F' P5 H# f+ Y! D- B, @8 L' N' x; Q- I
set-current-plot-pen "lorenz"0 z1 U4 D' K7 \- _. X% M) p
set-plot-pen-interval 100 / num-people# J& F2 s& w1 O3 Y. s
plot 0
W0 k, s! P; ^+ P: d. l) }$ \9 E5 N, D8 [
let sorted-wealths sort [wealth] of turtles
8 G' b: E$ h2 s5 @4 _ let total-wealth sum sorted-wealths8 u( i* ]6 u3 N+ ?$ N1 P+ }
let wealth-sum-so-far 0: U7 C& t) t$ {6 `* H( N
let index 04 T: R; J( s9 W6 N
let gini-index-reserve 01 ^% E$ ]* b/ w. K5 O' e1 r
% E1 h$ ]* ^% ]5 g
repeat num-people [. g+ [8 D) Q/ y, j" r
set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)
- o% ~! J* D0 L& e0 a plot (wealth-sum-so-far / total-wealth) * 100
0 V1 d2 Z, D7 V! O$ c7 ]+ u* w set index (index + 1), p: ^! }" O/ B# t- X8 {* t
set gini-index-reserve
7 A! k; ]* ?" m( r9 {+ T gini-index-reserve +
$ U- ^3 O* l6 g) L- p; [ (index / num-people) -$ e: B" ?4 i$ q; c1 I# u
(wealth-sum-so-far / total-wealth)
6 l# s/ }+ C/ a" v0 C ]
/ G; i3 y9 M: y. h6 o* b" g; \) }0 }; W8 G/ l s. O! Z
set-current-plot "Gini-Index v. Time"2 x& C1 `4 A$ h
plot (gini-index-reserve / num-people) / area-of-equality-triangle, W8 {" B0 z7 R4 n
end8 A |( e# y/ o, q9 ?5 S
to-report area-of-equality-triangle/ e3 Q* O4 r5 i/ D! G
report (num-people * (num-people - 1) / 2) / (num-people ^ 2)
; f% H* Q0 i' Y P# D4 P# z( X) Pend |