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, q0 _5 l ]9 \+ Z9 M+ X
globals
/ X# Y6 y$ M1 O: D5 A+ G[
, F( [8 V/ W; s" _, ]3 ?4 p# r max-grain ; X: _4 p6 N. C
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]
% T5 k- J6 G$ g% A% [' e- \2 O5 `! e. x+ ^
patches-own9 Y; j! U7 h/ E' A
[3 T; R/ R, L5 L% I
grain-here
( `! f4 S7 z/ v4 z0 R max-grain-here ! U, W$ \2 q* J
]
: |/ Y, P* w: I' Y
: p b5 ?) ^. Uturtles-own
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age
7 A' b2 M6 A/ Y5 g' b' E# Y! [4 x wealth 0 N2 \% p) D( x" P
life-expectancy 7 O8 n' @) I' a: C+ N
metabolism
5 M# [0 S3 [& G8 y7 Q2 o2 l vision
" O7 s+ J4 v0 _ k+ n inherited
+ {! K( j% t; } e: h4 X]- a2 W; n/ S" U$ L
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0 |# ?3 l# U: P2 {" _$ s, Ato setup
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set max-grain 50
+ C( G* f0 T+ R2 u+ j setup-patches" n& n, S K' }
setup-turtles
6 T6 |# ]. y* @9 W7 J# t setup-plots0 M Z' S6 n2 @3 r# l
update-plots6 Z$ F" H6 w+ C" Y* [1 `, S
end4 n6 v8 M3 b( \9 c
to setup-patches8 V5 u7 c9 l: d$ k* N
ask patches: R1 m2 P1 F! V" d, B
[ set max-grain-here 0& C2 V. Y6 A: ^6 o1 N0 X
if (random-float 100.0) <= percent-best-land
2 M: G3 R+ @: p0 G% }; _ [ set max-grain-here max-grain( ]- ^+ Q1 n* Z9 f5 c4 G
set grain-here max-grain-here ] ]% a% [3 N% n. k8 L- J7 K
repeat 5
+ h; ]# w, S, U) x8 p2 T R- F [ ask patches with [max-grain-here != 0]/ k4 h! \* }3 m8 J% A0 \& u" J" T
[ set grain-here max-grain-here ]
7 X7 H3 `, }) S5 y3 k0 E/ Q+ d$ q diffuse grain-here 0.5 ]
' Y9 D( F" o( M' K. ] repeat 10
0 O" e3 F* S/ j" @( x6 S# E [ diffuse grain-here 0.5]
" h$ w( [) I$ _- T) ] ask patches
+ d! ]" N7 z8 N1 O) T5 i# x [ set grain-here floor grain-here
5 d1 _: ~+ F9 B7 B: N9 m2 f set max-grain-here grain-here 1 ?0 x8 Q: u/ |' H' Q& N* w% H
recolor-patch ]' u0 S# B4 ]1 A2 V1 w9 ?2 p% b3 M
end/ ]- ~/ k$ y6 S' m0 D d- Z: q
to recolor-patch
) @: ~% o- F# { ~8 I set pcolor scale-color sky grain-here 0 max-grain
k: {& ~/ _( u( v$ z1 Nend# f$ G; F+ g* i& I- H
to setup-turtles4 d6 p0 w5 j2 k5 S$ C
set-default-shape turtles "person"
' u) k3 Z H" \8 q' v, l crt num-people& p; |7 K- Q+ W( q n o
[ move-to one-of patches - \$ o/ ^( f, E
set size 1.5
- p& N `0 v" w7 M+ c8 L: j: M set-initial-turtle-vars-age
& J! @( T6 j! w5 q+ J set-initial-turtle-vars-wealth+ A. D1 A8 T: v3 ~4 m" p( E/ u4 O. }9 L
set age random life-expectancy ]2 d7 G9 x1 i' } V4 u5 \ l2 E
recolor-turtles
+ z/ n) Z) K. G9 Uend
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to set-initial-turtle-vars-age
t- h; X/ }7 @ let max-wealth max [wealth] of turtles
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ifelse (wealth <= max-wealth / 3)
7 N2 n. i5 [- F/ _ [ set color red
! T1 @3 b4 v! U0 M1 G5 C set age 0
0 l; d2 t& }+ u6 d' H: _. r: I1 J! p face one-of neighbors4 0 r# U: S6 U X' c
set life-expectancy life-expectancy-min +
$ x, |/ |- }9 a. x3 c* s& q! M' z4 K random life-expectancy-max
4 }" K- }; f( T- |0 ? set metabolism random 1 + metabolism-low! R" M6 V: c3 @+ o9 Z L
set wealth metabolism + random 30
, T7 `* m/ ]+ K7 `2 j& ~ set vision 1 + random max-vision8 ]/ n6 T. D! s+ z! y C
set wealth wealth + Wealth-inherited-low ]/ L2 E7 D4 l. O' D) Y; s
[ ifelse (wealth <= (max-wealth * 2 / 3))
6 O/ l1 H$ l ?, B2 h# K [ set color yellow ( x, \1 r: ~; g# O, B1 Q- p
set age 0$ q7 {0 i) n) l) b) [
face one-of neighbors4 5 U& U& E8 e2 T- W. S ~
set life-expectancy life-expectancy-min +! u2 a9 k5 r6 L) f3 J" j
random life-expectancy-max + 1
5 Z/ K1 w' W/ g$ C1 V% x set metabolism 1 + random metabolism-mid
0 y4 Q4 X7 h1 C; o1 [8 ?2 \0 J' g set wealth metabolism + random 308 |& \7 ], T& Q
set vision 3 + random max-vision5 y# S% r7 z3 F" h3 U2 K
set wealth wealth + Wealth-inherited-mid] v3 X; p8 D9 {) h
[ set color green # P2 n3 s+ V7 u$ B; k/ h' V
set age 0
* d5 `4 x) {- z0 u; U9 ? face one-of neighbors4
# d$ {' ?7 H& w( C- B, r set life-expectancy life-expectancy-min +1 P8 f! Z( h7 ] N2 R; p) n5 G+ X
random life-expectancy-max + 2- ]5 n* H" [8 o! I3 A" a
set metabolism 2 + random metabolism-up, ]5 Y# i4 Z9 H; w. A( b
set wealth metabolism + random 30
1 N2 M* n2 t s! h' w set vision 3 + random max-vision$ E% @2 v7 v$ }9 n
set wealth wealth + Wealth-inherited-up ] ]
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4 J9 z6 w4 X# x5 R3 n2 vend
8 w9 K# M; s; ^ Y' \to set-initial-turtle-vars-wealth" s7 E1 q/ a1 Y( Q+ k9 B
let max-wealth max [wealth] of turtles
3 [1 n7 ^' P5 G3 s; U set age 0
6 h& F& D. j8 k% C, M6 o0 _' ?# f face one-of neighbors4 5 v) ^4 N2 C. G9 H
set life-expectancy life-expectancy-min +
) x. a" n1 |" o6 x% p! k2 w- j random life-expectancy-max
6 w5 g. D0 Y' K2 B/ f set metabolism 1 + random metabolism-up; h; M z1 X" w' f$ s- M
set wealth metabolism + random 30/ S% e& H1 G( |2 K" i
set vision 1 + random max-vision
. |8 H1 [% F0 i; G6 Oend6 R9 z- x* c' c) a F+ S7 a9 n+ o
to redistribution2 W% } q5 t2 ]6 d0 K9 _4 o- H% t
let max-wealth max [wealth] of turtles4 ^$ H6 P. A+ c! q. S8 ~
let min-wealth min [wealth] of turtles4 i; n7 t7 K( \9 w, S/ h0 d, y2 M! q+ A
if (wealth <= max-wealth / 3)
+ y! P$ ^8 x ]6 H6 K, v [set wealth wealth + Low-income-protection ]
* i3 i" `/ c6 [# P/ l$ Vend
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/ Z) [ _/ F1 Dto recolor-turtles
& j( y1 h, N; f: ~5 s5 y- f let max-wealth max [wealth] of turtles# g8 v: M7 _$ P1 v7 y1 h' t
ask turtles
/ k" i" L, l `$ p% O [ ifelse (wealth <= max-wealth / 3)- i; J$ @% R% j8 |! E* d- ?# ]
[ set color red ]
, k; E& |% q6 s% E [ ifelse (wealth <= (max-wealth * 2 / 3))* d) N! n+ `$ ~! e
[ set color yellow ]0 t& I( N- l5 i* I! E
[ set color green ] ] ]
" i6 c+ h% `6 R0 P' n0 W0 ? ask turtles [ifelse show-wealth?" Y2 w6 u: X4 a' t2 D/ ?0 B( z( B
[ set label wealth ]
8 e* _/ y. v/ b$ N5 _1 F. ~ [ set label "" ]]$ r7 I; } b! D5 }* O" i
end
4 w0 X" b( P w: ~
5 _ ?6 J1 c0 k ^. [to go
9 E+ u) h9 B( d4 ~+ w5 ^5 ` ask turtles3 @ a% G8 X; n, I9 L i# [5 i
[ turn-towards-grain ] & Y* T; B" `' I0 ?3 L; t8 Y
harvest* f. A$ \( r9 s% ~/ a/ M% t
ask turtles
. L. w, t* q4 M2 y+ o/ N- ?+ p [ move-eat-age-die ]) d0 N3 R0 y! D) c
recolor-turtles
( J! w0 {; [7 O9 u+ X7 b if ticks mod grain-growth-interval = 06 i7 K0 }. R* f9 D. s7 c
[ ask patches [ grow-grain ] ]! P7 }$ u$ I% J. b9 W
, x8 o& q& l/ h% e& ^ if ticks mod 11 = 0( h, H+ Z C$ d- a' i! s. t
[ask turtles
: ~; x3 r2 Y) i! H% c [ redistribution ]]
3 q" v5 l( y! y& ], {+ e if ticks mod 5 = 0% I" _! F1 l K, j2 E; A3 g
[ask turtles- R6 W, n2 v* }" e: h& d
[ visions ]]
. f) Q# g5 H. H: h* k tick4 m5 R- _$ e7 W0 ^
update-plots
+ W' A) k. x1 e- V; s* P# Bend
M7 m% P! @4 T. P Rto visions
2 w* d( \1 c/ s/ f$ w' q set vision vision + 1 - |/ t3 j. z( m$ j9 i( O u! E
end9 f. @* V' w6 N/ J# B
; _9 X2 w6 T2 Y; @0 k5 j& ]
9 ?, v: X, v9 R6 J" k" a! r. a5 ]2 ~: B( J
to turn-towards-grain , G7 x, X6 c: L5 \
set heading 08 I5 r/ F9 N" J8 G. @
let best-direction 0" p. d; o2 j( y! ]$ M7 @5 p9 K
let best-amount grain-ahead
+ T7 R3 [* |4 v: C* @( u set heading 900 y }3 [6 q; x2 q% {0 _
if (grain-ahead > best-amount)$ ]2 X; d0 n0 n0 Z* J6 t4 X/ a1 [
[ set best-direction 90. z/ o2 z7 h3 }% f& u# c' A
set best-amount grain-ahead ]
$ t. y) |3 U/ H( ]' }4 w set heading 180
1 _( z3 r7 b* p* F: g: c0 H if (grain-ahead > best-amount)& y6 G( T, r z" B
[ set best-direction 180
' P. a, ~, q0 [' b' i, c set best-amount grain-ahead ]: I$ k! s. v9 X& j \# \5 N
set heading 270
7 R6 L9 r8 `7 k0 \. y6 ?3 q if (grain-ahead > best-amount)2 b A' ^" L5 ^7 G U
[ set best-direction 270
, j5 r! R6 w) H" A8 L! v set best-amount grain-ahead ]
+ {) n3 _$ q8 w, N# E U set heading best-direction! I- e" J* G' X7 b* Q0 u- J
end! T. N) H; `3 F
+ q) _! c! C! p' W! B8 n( Q
9 M0 g9 Q f3 @0 g+ ?
to-report grain-ahead
$ k: }5 G+ h6 z+ I1 N9 v0 e6 Z- f$ j let total 00 Q" b' R# m {: l
let how-far 1
; V) o0 P/ Q, E, X% I repeat vision' [( \) Z4 o" w, m* U
[ set total total + [grain-here] of patch-ahead how-far
: C; ^- n) z; \ set how-far how-far + 1 ]7 x9 M$ q6 R( e z; x( O
report total
. g$ c: b1 N* L& q- i. Z. a# V2 r+ N0 t9 yend
8 R6 h! w3 D }7 v" T6 ?1 K% i3 K+ ~6 |- ~4 ?* r4 \4 J
to grow-grain ) W+ ^; |1 C! y, R* f
if (grain-here < max-grain-here)
- j) m2 r( @% J6 T. f% @9 i8 [; H [ set grain-here grain-here + num-grain-grown
) l& l7 u/ n# O( t; w if (grain-here > max-grain-here) - i' ~% S3 h- L9 J5 B! G
[ set grain-here max-grain-here ]- A! C, z4 y; F2 e: ^) w
recolor-patch ]
$ G+ @) y) R9 {0 V4 e- a& y/ c/ ?7 kend
, ^2 n2 R: n' A6 M' pto harvest
5 y& P j# i. ^( X' ~3 U ask turtles
) @; C' C- Z% i4 q& F0 N- r* q [ set wealth floor (wealth + (grain-here / (count turtles-here))) ]
' G' Z1 F' a$ ` ask turtles3 C1 X/ l& v9 l9 @/ V
[ set grain-here 0
' D* {& r8 \. I recolor-patch ]
1 |9 ]. W6 w1 D% n
$ F$ U. ?7 h' ^( _( m2 _- \end" e8 ~' \" @8 V/ [3 h
' L/ O9 p$ m( v9 T9 J& o
to move-eat-age-die ) }3 m# R/ J, p6 Q2 ?: N
fd 1
# ~2 r6 }9 O, f- D3 _ set wealth (wealth - metabolism)4 i" s4 H8 w5 B W
set age (age + 1)8 T& c6 j& z9 j" B' @
if (age >= life-expectancy)
7 \5 n8 W: i8 b- P q [ set-initial-turtle-vars-age ]/ O) [" f4 I+ a1 U( P5 y
if (wealth < 0)
$ I3 p( A2 X4 o( Y- }, ?* Z [ set-initial-turtle-vars-wealth ]
0 H! i t) U1 y" e" \ 1 s) N. n/ N! e- ~" o. G+ ]: Q8 I7 S
end' u, t' u# `+ A* F
/ I5 k" e3 }- e
6 p) B9 ^6 s, u! {3 H: [% [+ {6 X/ zto setup-plots
! l7 |. V) C& a6 J' c set-current-plot "Class Plot"3 s: h0 g, J. O- |) q) X# f
set-plot-y-range 0 num-people
/ {8 G: V5 {" X. z& } set-current-plot "Class Histogram"
/ g$ M: F9 _0 R4 C1 D3 k set-plot-y-range 0 num-people p/ i* F# [& e; J f3 |" V
end
) X) I: Q& ^& u: V, J
4 _6 ]9 F7 q0 Eto update-plots
" `3 B9 M+ M5 j( H) I update-class-plot
$ M2 j4 S6 \& m/ C2 t" ]+ t update-class-histogram
, l3 a, v6 _ f3 ^1 r update-lorenz-and-gini-plots
& ^) g9 }( A) ?. zend
5 V! t$ d/ T" [5 O! C& w z6 U. m" M5 J& e X0 K
to update-class-plot
; Z" W) o: k5 _" d1 K; I set-current-plot "Class Plot"
3 i+ r$ W$ J4 K- [" Q, R set-current-plot-pen "low"
3 |! [: J7 i- l8 J2 l" Z# W+ c plot count turtles with [color = red]0 `% A* }7 N" Q6 c; x
set-current-plot-pen "mid" ~0 B8 I1 J3 R6 Z
plot count turtles with [color = yellow]/ m/ V5 S6 i$ b& x0 W
set-current-plot-pen "up"/ m8 C$ W! o% d9 L
plot count turtles with [color = green]
* m. ^4 ^6 \: e6 vend" O& B0 T0 d+ Y; ?5 u
W: Z/ r9 f# y3 u; kto update-class-histogram* G( C4 p1 d# C
set-current-plot "Class Histogram"
h: \$ n3 D5 l) ` plot-pen-reset
7 ]& ?, L! j1 L5 _$ h/ J) k6 U set-plot-pen-color red6 d- a' l8 l& X
plot count turtles with [color = red]+ P3 d# G2 N0 v8 U. C3 D$ I
set-plot-pen-color yellow. Q9 y/ A& f2 f) [: g7 y2 J( `% s( u% _
plot count turtles with [color = yellow]" k/ ?- Z$ t8 x$ k0 u m4 n- y5 \
set-plot-pen-color green
8 c/ d) t/ B, K. ] X plot count turtles with [color = green]
" O; y7 n, h' \2 N1 A/ X+ nend
9 M& g! X1 c2 T) Xto update-lorenz-and-gini-plots
3 W2 ]' q: i8 c e1 }) a S set-current-plot "Lorenz Curve"5 \5 l: t2 J' u0 E* q; r) r5 D
clear-plot
8 W; ~" ?; P; f% h( o$ |5 |, x( h+ G: M- r, F
set-current-plot-pen "equal"
6 ~% I" ]# n- G; U% \* _ plot 0+ e! V, P' X+ _ n
plot 100' R5 H/ |- n) d8 S. ^! }) @2 m
: `6 V( N: x! N9 a& _
set-current-plot-pen "lorenz"
, P, X9 W" f: w2 [/ t( ]; a& ~ set-plot-pen-interval 100 / num-people
0 T! \, f) b! c0 j& v% _ plot 0
' j- \5 U: E3 Z& ~2 m! Y3 s9 u6 i$ C$ |: o4 s# g; z8 V' O6 B
let sorted-wealths sort [wealth] of turtles+ Y1 }7 W5 y; U* W
let total-wealth sum sorted-wealths- a2 s2 q2 j1 l4 F' A0 d
let wealth-sum-so-far 0
: a2 F% f8 D) |/ ], Y let index 0( Z o1 ^: J9 M
let gini-index-reserve 0; ~. E' w2 I4 j" a2 g* U6 D
, k. f4 j; Z$ g4 c4 i
repeat num-people [0 M, O( p4 l& J% X$ d9 k
set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)- a! a: u+ O( [3 u c, l
plot (wealth-sum-so-far / total-wealth) * 100
& H$ j1 P6 y7 n/ [+ `9 } set index (index + 1)' ~# e# x1 l, q7 E; ]1 [
set gini-index-reserve" J+ l$ |$ L4 ^
gini-index-reserve +# U3 I9 b8 \9 Q2 v. h
(index / num-people) -
( f: o' Q9 _8 S7 d% {& w. o (wealth-sum-so-far / total-wealth)
& Y' J$ B& X% g0 O8 K! ~& @/ n' C) a ] V$ A' y. `- n
- @, |7 Q' |6 l' z6 M& n w. p9 L
set-current-plot "Gini-Index v. Time"
! r; g4 p. A% x4 b9 K plot (gini-index-reserve / num-people) / area-of-equality-triangle
6 g! \; L L1 E t% a Z' ^end
6 V8 C4 S P3 e/ hto-report area-of-equality-triangle
$ W* S5 b7 @1 |, ?. _; F1 p O. V report (num-people * (num-people - 1) / 2) / (num-people ^ 2)5 d$ n- `2 S" N! S0 r* u# g- T' K
end |