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5 g; [' M' I2 v1 v' i% K7 o2 S
globals
( S3 _2 G9 Q) v[
7 D3 p6 k7 E2 W0 ^1 L, U$ Z9 g max-grain
/ O9 N0 A" C" c8 ?/ ~
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W" j. s% P/ p2 d7 a3 c x( _
patches-own
2 \' M; t+ B/ j/ M[
8 q8 z- |* w6 x/ X- r, x grain-here 7 P& y" b* W# K% R. Y' j% ^
max-grain-here
6 s! ?0 f0 e, u& D* C0 D i# H. b]. k/ {3 N0 ]- _) T1 `9 w: ^" P
' O5 a9 w7 Y) d8 Z9 f9 @# O, M! A( A
turtles-own4 n. ~7 d9 v/ w0 k2 t2 x( F0 O
[
/ i$ i/ i1 {% L$ [' q# B age
7 T y2 J, l4 I' I) ~ wealth / ~5 @) g/ O( p6 V: ~! N8 @! x$ g
life-expectancy
6 N6 T" n( J) k' C3 Q metabolism * |7 p# Q9 b. f! W$ U, v
vision
2 K T# Y- L/ m) ~7 ]9 A1 w0 o4 K5 w inherited $ i S8 `* j1 A
]
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2 C5 d0 ] l) k5 f/ P7 ^ D0 ?6 X' J
to setup$ ~) V0 I6 n) o
ca8 s" f) ~) P* k( @6 D# U
set max-grain 50
2 t. {2 c+ I3 @" k) d) a' p$ V4 e5 _. C setup-patches
2 v R8 X' r: Z' R3 ?' s6 w! Z% d, M setup-turtles
0 G; L) @6 j8 g( q setup-plots
: a5 u* c2 C$ j update-plots
1 O' m/ x: I2 `2 I9 z& m& Kend
) ?, V( J' j. w$ B2 q! g% Oto setup-patches4 ~% C! ~6 H# p6 X8 F) H
ask patches
4 j: {% ?" B8 n( M, y" u. A3 m8 l [ set max-grain-here 0
- q, c4 d% {/ \% {& d if (random-float 100.0) <= percent-best-land
1 r% k2 I% ?0 L, z8 s [ set max-grain-here max-grain' g9 \% H8 E( e, x- c. w4 \
set grain-here max-grain-here ] ]
4 k# `: t! o( i/ l repeat 5
6 Q- t6 i7 b7 T [ ask patches with [max-grain-here != 0]
8 \( ?4 w/ ~0 V3 Y! ~ [ set grain-here max-grain-here ]0 @4 j( R" |2 j% Z& K5 ~. }
diffuse grain-here 0.5 ]
3 _8 o! V8 m! S( P' H6 H$ z( B repeat 108 G X$ k; P# {$ i( f
[ diffuse grain-here 0.5] ( b* \- I' ?! X1 j
ask patches
8 u6 l0 b$ \7 T/ M& ` [ set grain-here floor grain-here : ?) B, x7 X8 C- p1 p9 q
set max-grain-here grain-here 1 K2 a- k: [* b4 w, C( h
recolor-patch ]* S3 ?+ `+ J( I% a; m
end
! V) R, ~: V% v: T7 u2 ]to recolor-patch
1 _( M$ ~' Y6 c8 A6 |" H5 O set pcolor scale-color sky grain-here 0 max-grain
' U3 g. N# F& ~8 Y. z6 Pend
( s% b# H3 B" ?( e7 u0 ~to setup-turtles
* q2 j1 ]* b6 t1 p. Y: A- g set-default-shape turtles "person"* K) }# l- N9 _4 d* W2 d' a+ @7 m3 S
crt num-people
2 ]+ D1 [0 g7 J4 }3 C [ move-to one-of patches ' a+ ~ \! f* T3 x: Z b1 Y/ y8 d
set size 1.5
4 R3 W" g% f! t# K1 Q! u& U" x set-initial-turtle-vars-age) j5 E- F2 Y# O( k
set-initial-turtle-vars-wealth4 S6 k% R0 s# n9 @1 {5 C: _7 I7 [/ t. n
set age random life-expectancy ]
2 G1 P1 g3 `. h; F7 z: v recolor-turtles
3 H/ x: g. r, E3 `- Oend
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to set-initial-turtle-vars-age$ `* t+ h8 L: e9 H7 d$ c
let max-wealth max [wealth] of turtles
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( a9 n: L. _2 m8 f ifelse (wealth <= max-wealth / 3)$ g2 ]7 A6 J+ a9 J0 @- \# U/ h1 t/ a
[ set color red
) S$ ]3 x; I8 p/ _2 t/ j set age 0; { f6 P( H" Q8 d
face one-of neighbors4
4 D0 P4 u" W" h8 R1 m A set life-expectancy life-expectancy-min + ^$ X9 ]( Z. ?( `
random life-expectancy-max % _( j! z" h4 y' Q* B- V+ Z& ?2 |
set metabolism random 1 + metabolism-low
# d/ p( O( [. O0 B9 u set wealth metabolism + random 30
* r d8 B0 k/ n$ E set vision 1 + random max-vision' b! D! _: G1 `/ M5 A! U# @; o
set wealth wealth + Wealth-inherited-low ]" W y, d N$ W$ N+ m! W+ E
[ ifelse (wealth <= (max-wealth * 2 / 3))* f, w- B! w0 `' x
[ set color yellow
" Q4 j3 T9 v& X( S7 `. X3 _. S) G! K9 g set age 0
' E/ e# b" h% ~! X! T face one-of neighbors4
" |) x) w# U$ K set life-expectancy life-expectancy-min +
: k! G# y9 P* o' a9 b8 Z1 S" H random life-expectancy-max + 1! m7 Z1 u6 o+ K/ L
set metabolism 1 + random metabolism-mid
7 H9 q# _$ E+ g4 l5 y. I" ^/ { set wealth metabolism + random 30. n' x! z( ]( D. ]1 v+ _/ H
set vision 3 + random max-vision
- `$ i- M X" L n set wealth wealth + Wealth-inherited-mid]& E: ` S2 o0 }- {) l9 X8 w( o
[ set color green z+ J# w9 A% I9 w0 e* P* A- I
set age 0
9 V! h5 S" k" T8 L/ B3 p face one-of neighbors4 " s! }! A5 S' H, E1 v# i, e
set life-expectancy life-expectancy-min +$ c1 v) A7 h. v5 ^6 o
random life-expectancy-max + 2
# T' H: L5 S* S' ~ set metabolism 2 + random metabolism-up1 p6 @ U0 l8 e! C2 Y* H4 e' ]: |7 J" S
set wealth metabolism + random 30
9 Y4 h/ T* W& v6 N set vision 3 + random max-vision
P% Y; Q$ e5 u6 q$ C set wealth wealth + Wealth-inherited-up ] ]
n: A( A4 P& t5 e 6 i- K k: ~ @
end
0 @; l N% t* k2 H6 B/ b2 |0 B2 Hto set-initial-turtle-vars-wealth8 p! A8 {+ {9 i. D! m# i4 w i# f
let max-wealth max [wealth] of turtles
6 v. H, o1 E' ]/ }6 E; O set age 0
& o! f3 g" C# M3 F) H! N7 P face one-of neighbors4 % z' s4 X, R! M
set life-expectancy life-expectancy-min +$ M" T: r! {, T# M
random life-expectancy-max 4 r# K$ n5 ]) z
set metabolism 1 + random metabolism-up
( y1 r. H; @; g# f; O set wealth metabolism + random 30' t: C: ~- ?1 w6 w9 n' Q
set vision 1 + random max-vision
3 f) `, i! ?1 `/ C) ?end
" R9 R# V. D/ N S9 T% Vto redistribution
6 U* W6 \0 {3 Vlet max-wealth max [wealth] of turtles
' k! F/ K3 Y/ \4 \let min-wealth min [wealth] of turtles
% b" L. h' H* \$ {; _; Tif (wealth <= max-wealth / 3)
4 z8 s0 B5 _1 {$ |/ K( O [set wealth wealth + Low-income-protection ]0 {/ q! [& v. Z8 h/ |
end/ L5 W6 d( {9 S5 ?2 k7 w* S
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to recolor-turtles" D. s# T% Y' [4 t" p
let max-wealth max [wealth] of turtles
1 F2 K9 G4 Q8 w m ask turtles6 N" F2 b9 E R1 B, \: ^4 S
[ ifelse (wealth <= max-wealth / 3)
2 T; C2 t# K9 H( y4 B8 M [ set color red ]
) }- U" \4 w0 ]9 q8 u [ ifelse (wealth <= (max-wealth * 2 / 3))1 _! D2 L$ G/ S. Q/ m
[ set color yellow ]
: J$ s" F, J3 V% v [ set color green ] ] ]
- ^$ ^/ F; b9 D& z ask turtles [ifelse show-wealth?
) j' f: y: k: G& A# R$ W [ set label wealth ]
* B7 n! O3 g9 [ k/ @ [ set label "" ]]
' F. b2 }- s* w1 P# I& yend
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to go( L$ t! I. s3 R! C) t; ]
ask turtles
: }7 P. a7 a. z7 M [ turn-towards-grain ]
+ A' b0 q! ?2 I harvest6 _ Z4 ~+ | Z; U% E3 H
ask turtles
) r8 s& v& y0 N- `1 z& j [ move-eat-age-die ]
0 T) g/ M' c7 r, u7 S recolor-turtles8 q0 V# M% C4 t, v; V B
if ticks mod grain-growth-interval = 0
8 _) X& z5 @4 t, R [ ask patches [ grow-grain ] ]
4 ?) y v4 G5 F/ l! o
/ b# T$ ^) K/ ^% ^ if ticks mod 11 = 03 `7 R* R7 a7 v3 z
[ask turtles" E' J0 ~! k0 A' ^' K) U9 }8 ^& y
[ redistribution ]]
+ Q f: \. ^4 n# j* @ if ticks mod 5 = 05 |/ p3 L; ]+ J0 z
[ask turtles
c( S6 J1 ^, q4 Q [ visions ]]
, Q! M" I. u$ ^9 I4 Y" c tick
3 x: r e' O" ^6 D7 N2 d update-plots. e0 U" k) V* \( |" x
end# ]3 y2 M w1 a9 P% u5 J% F' S( c7 ?
to visions
" k. C H; Z$ h+ h( o$ B: G set vision vision + 1
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7 t) i! u; j* P5 a0 u. Y0 p: ?* L ]! R& u: Z4 e: t
* y% ?# U/ a& t) Y# A5 h
to turn-towards-grain
8 k4 v$ M4 U& E& k# b6 e# _ set heading 0
0 V/ L4 r/ Q+ B. Q let best-direction 0: Y9 C4 e$ x+ E7 Q
let best-amount grain-ahead0 {) K" ?+ n' e. g) L2 h- u5 B1 Z2 `
set heading 903 M1 W: ~0 f. ]8 L" g, H1 X
if (grain-ahead > best-amount)
. S) }8 `+ o2 ]+ h [ set best-direction 90' S! a# O6 k/ U4 R5 j, C& Z
set best-amount grain-ahead ]
! P" W# K( g/ q" n- K set heading 180( R# T. d6 {/ ~. m" j7 s
if (grain-ahead > best-amount)
; h8 Z: d3 \% o, ^! h9 w [ set best-direction 180
* i; E, l7 w8 t& Z: k* m; p8 _2 M set best-amount grain-ahead ], V* n& c( F. X; D
set heading 2700 ~+ P: r) k% w# d) |+ A
if (grain-ahead > best-amount)
; p" B8 Y y* Q; s( z [ set best-direction 270
- G' v$ ^7 y& }) O set best-amount grain-ahead ]
' @+ v% t3 H$ l# S9 j! D; s set heading best-direction
8 a8 H+ M7 \0 r5 Z3 A" R5 W1 {" kend+ e+ Q) d' h" P
& l# {1 L+ ]8 K& @/ B& l3 O# w
2 |9 E0 e0 E: O1 y* F' gto-report grain-ahead 8 @( P: r) g/ }& H( J2 r! U( v
let total 0$ G; A+ M* {7 t( N& ?+ h
let how-far 1# N: Z$ g, Y) ]% e. Y
repeat vision
8 B* p/ _" ]% B+ M [ set total total + [grain-here] of patch-ahead how-far, l" J: `7 ?, h( W/ h2 O7 _6 W
set how-far how-far + 1 ]
7 |% N' B, e* A$ H; r report total
( j1 V0 D q. i" h/ bend7 b! g9 V6 [& ]3 x# D' _
$ B5 T6 H; i) \8 I3 a- M
to grow-grain 6 O. ? T% [; B. \2 _
if (grain-here < max-grain-here)( Y* g$ E; u" e$ z1 h
[ set grain-here grain-here + num-grain-grown
, J. v8 {: t+ i* F: ~! ^ if (grain-here > max-grain-here) , X( G6 z X( @% L) ?
[ set grain-here max-grain-here ]2 S# a) [) P, j8 u. a- z
recolor-patch ]( `1 G8 j7 {" h8 s- {
end; v4 B) N& v) h7 d# c; r" J6 S
to harvest
2 u# q2 t G3 [0 J+ Y5 Z ask turtles" v2 Y+ h; g4 M: ~. x- G; { o, a
[ set wealth floor (wealth + (grain-here / (count turtles-here))) ]
1 w* O0 Y0 O# g9 G% b% E, N- e ask turtles. x' E% u5 F) n! @- Q+ O, i8 H9 @
[ set grain-here 0: x& d+ Z0 j" w0 _, E8 u: h4 ^
recolor-patch ]: D" X. p: Q$ W9 Z$ S s6 r- I2 @1 k: ]
' r! t0 R x3 {9 `end; ~( p3 q$ G! ^5 B$ J
4 C6 i! F& B5 Y' g/ Hto move-eat-age-die
* ~8 Y9 v8 R1 d! Z; e3 p% { fd 1( w, j: W. H. W; Z) e
set wealth (wealth - metabolism)6 n2 [, Y6 F( w- M# U: y" s V
set age (age + 1): r: l3 @; y6 Y' B. j
if (age >= life-expectancy), u& O5 b1 B- m! z
[ set-initial-turtle-vars-age ]
( ^( q. c. O% L8 O# y* z if (wealth < 0)
_! K w1 `6 M# F, w. y$ w- ~ [ set-initial-turtle-vars-wealth ]
( e+ q! e8 l9 b( Z- }9 p
5 s4 P2 {) u2 C* l3 xend
( c1 A" O6 e4 t/ \' V
3 \9 [; K" [0 _; e" k
: B# \7 z: e0 }% q% ^to setup-plots2 M1 F$ y. A9 p+ r9 O+ _9 D2 V
set-current-plot "Class Plot"" W# j# W n6 |" q( J- J' w
set-plot-y-range 0 num-people& Y: ?2 j" g# o. v0 o, M# M" g
set-current-plot "Class Histogram"
$ X! ?% O/ G$ D$ @0 U7 C set-plot-y-range 0 num-people
* u! c/ [) e( a% x3 Nend% G) \1 f: |- _2 I. C0 D
) Y8 j& U7 W$ q& C7 R
to update-plots
: |; K3 p4 x- y6 O: m update-class-plot
% O) F, ^ {9 L update-class-histogram1 I1 q D4 C$ m, X
update-lorenz-and-gini-plots! b' Q: g% K" X' O* K# I+ g
end
j7 [% g' E* C: y
. u" Q" W; Y( ^( n' V# v ?to update-class-plot! {+ z, Z% |- t& g( F6 C9 m( R
set-current-plot "Class Plot"
# f0 ^2 V( z8 S* N1 E set-current-plot-pen "low"( d+ K/ k# m% i
plot count turtles with [color = red]
" y: y$ b: l( d! v: s' I( Y& c set-current-plot-pen "mid"7 g8 m, \/ f- W+ A0 F: Q
plot count turtles with [color = yellow]
8 N7 ?% H$ t$ I" [8 W9 s( { set-current-plot-pen "up"9 w$ s- i- O$ V. f6 A2 V- c
plot count turtles with [color = green]
0 v! g1 L" S: ?- B( Dend
* P6 c' k) F" Y" g
' U, B( U0 c8 {to update-class-histogram0 J! V& D, |* q" }
set-current-plot "Class Histogram"8 C* L9 d% }3 K- Q# ^0 ~9 ^
plot-pen-reset
" o$ [9 J& e; U set-plot-pen-color red
& \% @! i( z4 k2 z- O+ ]2 I* _ plot count turtles with [color = red]
; A4 D0 x) G% e set-plot-pen-color yellow
. e* D' b# ]( e5 j) ]+ `1 ` plot count turtles with [color = yellow]
3 R. Z% s; @, P/ L# k: K0 {( X set-plot-pen-color green
3 g6 _0 H8 t4 \. {3 r- a2 I plot count turtles with [color = green]
7 @' ]$ o' O0 aend1 A( U% h, G( K
to update-lorenz-and-gini-plots9 a4 Y4 I6 u$ U1 m# h d5 U: e
set-current-plot "Lorenz Curve"2 c) q+ B/ `$ w6 A
clear-plot
* _5 ?3 l M" n( z8 n* `/ C" w( r( Q- W. w1 E1 [2 P5 c- [
set-current-plot-pen "equal"
0 K1 W9 R& @8 M: g5 _7 E, \ plot 0! ]1 Q5 [* ~0 I p, T# h! ~
plot 100
9 E. Q7 v F: L, \/ R; o- g5 n8 n1 t4 t
set-current-plot-pen "lorenz". {6 d" x b- L/ m3 n: u
set-plot-pen-interval 100 / num-people
/ _; ?8 Q6 Y' K plot 0
{+ ?+ c" m# f
/ M6 B! x% g* W- j* N. o& ? let sorted-wealths sort [wealth] of turtles
* f) @; C. A. v; I1 q( y) ` z0 N let total-wealth sum sorted-wealths% C8 k+ o/ G& W- i
let wealth-sum-so-far 0$ n1 \% I! t& M0 z6 a6 s
let index 0* q3 k2 C* R- p! E9 _% u
let gini-index-reserve 0
3 ` l9 H, Z9 x, Q# l% G: ]! ^& o/ b# o2 t0 f7 w; B. B, C) a4 F/ F- L) x
repeat num-people [$ d6 }" l4 l0 u H9 V9 E
set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)/ L/ C. B9 ?6 _; F5 ^$ |, n
plot (wealth-sum-so-far / total-wealth) * 100
L! l0 d% T( B% @. } set index (index + 1)2 c8 T2 M& F8 ~3 n& z s t
set gini-index-reserve
1 V' R3 Q2 ?: }1 w gini-index-reserve +4 O( }# b5 k+ j, g5 a. H
(index / num-people) -1 p& _2 e3 ? ]9 o% Q* C
(wealth-sum-so-far / total-wealth), z( x7 k4 L! N5 ]0 X: _4 T
]1 T8 L/ \3 j! _# f0 s
; r! U4 ~ U' `- @; ?
set-current-plot "Gini-Index v. Time"
" P3 A0 I( D+ Q; |7 ?, q! b8 G plot (gini-index-reserve / num-people) / area-of-equality-triangle
! Z) D- i, g( G* \5 y7 x, Cend2 s' f/ |9 f& N3 v5 {/ E% K1 O7 O+ ^
to-report area-of-equality-triangle, g/ G9 U& X8 M6 }6 V( P
report (num-people * (num-people - 1) / 2) / (num-people ^ 2)/ ^; H3 l0 _8 t4 F# [
end |