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# F. x) z+ y9 B; }
globals
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max-grain
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]( W) C$ N/ \6 W ]8 ~, P! Y2 m+ {# C
) ]+ `" H- d6 N3 I6 j9 _patches-own
$ ^# q* t' u0 ~- b& r, `[
( m! R6 ^& d6 t9 _# x grain-here " `, a) B6 Y f; ?, b# s
max-grain-here
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turtles-own
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: h/ Q4 E0 @% j% i8 u. l age
% w- u9 S# H* J( h8 W wealth / B& g7 I* E) _& m S
life-expectancy M* m2 U+ @" x
metabolism : ]( D0 [# |6 `7 D6 \
vision- P3 c7 ^# a% `& ?( {
inherited 1 Y7 |5 h% ~! a
]
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to setup7 w+ f V: T2 h; m3 v
ca) i, B$ F) y- n7 l
set max-grain 504 \# p/ m [' _- |
setup-patches, k, A6 m) B! b1 O1 K2 | O
setup-turtles
" h, ?& p! ?6 N3 [ setup-plots6 B7 m" D$ ]/ g4 C2 {( L! w
update-plots
0 f: q( W& C) W. z: nend
, s9 o; B4 s8 x* z% y2 c, Tto setup-patches8 F" X% ^0 @ O. J4 ~& e, q
ask patches1 q. d k, _5 t. f ]
[ set max-grain-here 0
6 u6 W: [* L2 C# Q if (random-float 100.0) <= percent-best-land/ H: B6 w3 Q+ H- \/ O
[ set max-grain-here max-grain
" f' _1 y: K, d j1 e( z set grain-here max-grain-here ] ]5 @ ?4 {2 i3 z* S- q" }) F
repeat 5
4 F- O0 K8 C: z& U% S1 R [ ask patches with [max-grain-here != 0]! }6 K. a. ~% L6 e" e) z# B! T& }
[ set grain-here max-grain-here ]+ e/ {$ W4 x [* M
diffuse grain-here 0.5 ]( g- H, n4 h; b! ^( Q9 O2 C
repeat 10
4 A L3 y# E5 }+ z- s& t [ diffuse grain-here 0.5]
8 \* L7 H3 U+ Y- u/ n% M ask patches
' n) P% v: ~1 O5 S9 Q7 W z# S [ set grain-here floor grain-here 9 ?7 N6 P9 y1 i8 |. |( c4 _# l
set max-grain-here grain-here
" K: H0 p; N; n' k* F; R recolor-patch ]" G! X5 b) H7 w" c* f \
end! f; X' B3 e4 q7 {' V0 ~
to recolor-patch 9 D8 j" V2 t' }6 U$ s* M
set pcolor scale-color sky grain-here 0 max-grain
$ r' E& x! Q5 c! ^, @end
6 B7 }: b# r/ N2 L0 F/ d. Z( Gto setup-turtles; C/ N+ t2 Q9 I
set-default-shape turtles "person"
% |3 s( t" D3 ?( Z+ N; {# |% Y crt num-people
3 S, w8 g9 a3 \ ]# i+ V [ move-to one-of patches
5 }/ i7 ~( i& g( u' x- z set size 1.5
# i( n5 @0 C% n set-initial-turtle-vars-age
2 a2 z8 s) C4 G1 I) X4 }5 @% @7 k set-initial-turtle-vars-wealth
0 N( d8 X) o v0 `4 K; S set age random life-expectancy ]
' R" T$ G/ ?. E1 Q2 f0 R recolor-turtles- h7 L$ I$ U G# h9 [
end6 |' R3 ]8 v- r% G, X9 h# ?
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to set-initial-turtle-vars-age
, ~2 m8 R' I/ ^/ T0 _3 E+ c. W) ^ let max-wealth max [wealth] of turtles) |( P2 j0 F/ G4 T, j
0 O, z6 t' J$ f6 s/ f% M4 c ifelse (wealth <= max-wealth / 3)
- E+ R3 W; Q- U0 v, d, o4 ^% d [ set color red p+ ?: }$ Q" ~; c) u6 Z6 R3 ~' V
set age 0$ L# g' [* y" F) k7 G# W; U
face one-of neighbors4
! H- r+ t+ ^8 \0 ^1 r2 E# H set life-expectancy life-expectancy-min +
$ L2 P( n& \3 m8 w" e- ~' V random life-expectancy-max ( \8 ]$ q& \ _2 ]. r
set metabolism random 1 + metabolism-low
5 ]1 c, D; X$ v set wealth metabolism + random 30
; x% g: y- d0 r- A set vision 1 + random max-vision
, G: z! ]$ g+ M1 V set wealth wealth + Wealth-inherited-low ]
+ \. D. u, D. Y" N. c [ ifelse (wealth <= (max-wealth * 2 / 3))7 f) Q" D8 Z% g B
[ set color yellow
) m* N; K, j0 G) ~; t set age 0
* @ `# H; i' p face one-of neighbors4
$ f# Q0 s B( ~' A4 | set life-expectancy life-expectancy-min +% M/ Y, `8 B' Z" r3 _8 Q& D S0 a0 f
random life-expectancy-max + 1) Z D0 k; E1 M: i
set metabolism 1 + random metabolism-mid
7 ?0 O9 O2 c, S! U" Q* Y" E2 ~ set wealth metabolism + random 30; X# R4 R( G8 _; }
set vision 3 + random max-vision) T% g( P% c( z5 H% p
set wealth wealth + Wealth-inherited-mid]' L% {- M5 q& l5 S6 S
[ set color green
8 G5 K/ i2 r( e s6 \: H set age 0# C% a/ D/ ]( e/ T& n) A. T H
face one-of neighbors4
2 T. Y; F- v4 s0 z8 i set life-expectancy life-expectancy-min +
3 l1 N" k! `( H random life-expectancy-max + 2
! W* a6 I* o5 W) i% ?+ `2 e# d set metabolism 2 + random metabolism-up9 E2 ^% z7 i% B+ w
set wealth metabolism + random 30
" f4 `5 g/ x( y! Z6 H$ g+ u2 w set vision 3 + random max-vision
0 v: J! O1 d* j: z2 _ set wealth wealth + Wealth-inherited-up ] ]
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% p, @0 n% p3 k/ c; Hend
8 m# r6 N( a9 h- B$ Mto set-initial-turtle-vars-wealth
: N {5 X! f' E4 l let max-wealth max [wealth] of turtles
$ x0 b4 _+ [' \; x9 W0 h set age 0
5 ~$ d B% ]7 j& r$ n: J7 z face one-of neighbors4
. N# Z: h8 n' W4 u7 A% k set life-expectancy life-expectancy-min +
. \$ f# Q& ` E5 P( z) A random life-expectancy-max
9 _: R7 \( Y; Z; f set metabolism 1 + random metabolism-up
: ^( I# G+ D R0 V, e2 }$ g* R set wealth metabolism + random 30 y2 K+ @7 ?3 z& k$ r2 X4 P
set vision 1 + random max-vision : }1 U* p# I* ^) S3 L3 H
end
2 T7 H$ C d; Z2 z# i! ^to redistribution
; P$ V0 ~& \% a. R$ E: wlet max-wealth max [wealth] of turtles- k- `, w/ H1 r
let min-wealth min [wealth] of turtles/ \' s4 l) V# T, s5 |
if (wealth <= max-wealth / 3)
8 n6 x7 I/ z4 r p" ] [set wealth wealth + Low-income-protection ]
5 x1 O9 i% c6 j+ _% f& p1 |5 send3 A/ P) d3 _6 i
8 d: F# @% f+ V/ @to recolor-turtles1 H# X1 w$ J- ? g; {: w' a
let max-wealth max [wealth] of turtles
3 [9 F0 o, W7 n1 E9 B0 U' u5 f# S4 R ask turtles5 n7 i2 W' `7 C. x1 n8 c& i
[ ifelse (wealth <= max-wealth / 3)- ^$ {5 ?' _7 K5 {6 N
[ set color red ]; C1 ?: t# ~: `; u' K* H; A
[ ifelse (wealth <= (max-wealth * 2 / 3))( u$ w1 O; ^* B& B' ]
[ set color yellow ]. Z0 U4 S' O) A. a D) p6 R4 Q
[ set color green ] ] ]6 S1 v( _( Z" b! R& V
ask turtles [ifelse show-wealth?6 X1 f; {; b* P6 b3 _+ f
[ set label wealth ]
" ^. j/ _+ q8 v* S5 p- ^! s [ set label "" ]]
9 x8 e; [( t+ S0 p; }end
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! ^! i0 q6 @3 ]8 `( t& m8 s8 Nto go0 s$ Y& v4 Z& F
ask turtles
' v) o0 u" d# O' I [ turn-towards-grain ]
6 w0 m! B- r2 z harvest
: C- w, C+ t" N6 K" j# T% L ask turtles
, ~ M, o O+ Z. y1 g5 X [ move-eat-age-die ]
5 u# q/ R) [2 z' D4 u! G, s recolor-turtles+ t) h6 ~1 \$ \
if ticks mod grain-growth-interval = 0
# D& z9 v3 d2 g1 E; w# q [ ask patches [ grow-grain ] ]
+ ^5 Y3 G3 l( N
; r# ?* r1 n2 d% y if ticks mod 11 = 06 R* r0 C/ X- U4 ]& L
[ask turtles Y2 e1 Q. G) _9 i& n5 }& ?
[ redistribution ]]
: H/ \7 b+ J. g% r if ticks mod 5 = 0
) Y& I5 d, V# a; _" c& Q! H: Z [ask turtles/ q" N1 i2 P$ {0 |: _& |- H4 S
[ visions ]]
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update-plots
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to visions
% M8 L. Q* }0 m% v set vision vision + 1
4 c3 M* m, y" h+ N' d8 a# ?end2 C7 H, A3 B- N, P
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to turn-towards-grain ! g& q) g3 @& E7 k' U! g0 ~/ l
set heading 04 ^! L# o, D: _2 H8 M
let best-direction 0
( U5 g7 O. r# o q3 { let best-amount grain-ahead3 v( c- A, Z$ X) K% E* i6 L
set heading 90
/ a/ T3 E6 J# J: ] if (grain-ahead > best-amount)
, M) [* q J% a+ Q, H! `; {* X [ set best-direction 90
, j3 F$ l4 h: f5 |4 m; U b set best-amount grain-ahead ]
4 D O5 ^3 a7 M. H' h$ N/ W: G set heading 180
6 N5 ? k' L, O% s5 K if (grain-ahead > best-amount)
5 Q( h8 l' D t7 M0 ] E [ set best-direction 180' Z' R ]0 x( n n
set best-amount grain-ahead ]
- O. O0 A5 n9 S1 \9 G set heading 270& w$ m- l# V9 e) }# G/ l
if (grain-ahead > best-amount)3 g( W. E' F2 V, y
[ set best-direction 270
- [- u+ L! ]4 ]* o- v set best-amount grain-ahead ]" \2 \; ?' {: d1 Q/ t6 |$ O! A
set heading best-direction
) D" l3 S! _" {3 x& M; Tend" S+ }% q6 Y! A! i) I
, B \3 I4 f8 g0 X$ c& ]
6 m4 i" Q u. M1 xto-report grain-ahead
: k ? m2 i0 x6 b% R3 ~ x0 j let total 0
* k% A( n+ X8 \; B7 J% x$ N2 | let how-far 14 H X+ l; U$ b
repeat vision
5 S9 D9 Q' w( O6 e7 Z5 A [ set total total + [grain-here] of patch-ahead how-far
9 I/ |, X: y, ?- Y3 }$ v2 Y: H4 \ set how-far how-far + 1 ]
* G& ^% z# }; S- _; A0 Q) F report total
1 ~1 v, J: G( O. \ bend
) }" L# {+ r; Q u0 [! d3 }7 `/ c+ K2 ^
to grow-grain
) O7 P1 E4 r) V" M7 u if (grain-here < max-grain-here)9 [/ y9 o; M2 e
[ set grain-here grain-here + num-grain-grown
y# Z/ n5 f6 l! U# ? if (grain-here > max-grain-here)
5 s8 Q: M6 z' J4 E' Z; E) U. M [ set grain-here max-grain-here ]
) ~6 B) r& ^/ z @. | recolor-patch ]
! ~" j, g5 L: Xend# w8 k9 m# Q8 v0 H' }0 A; D) v
to harvest' n8 Y& u4 H M- Q8 C: V9 \$ R9 N
ask turtles5 W. H8 E6 T8 C) U t( b
[ set wealth floor (wealth + (grain-here / (count turtles-here))) ]
4 v6 B, v: _" a9 N; i4 v ask turtles9 |3 Q n2 \7 Z3 S U+ f
[ set grain-here 0
# t6 N/ T: f% N, X9 W) { recolor-patch ]
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end5 H4 O( {3 {: }1 v
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to move-eat-age-die
9 x$ I# ~6 E; o/ N& x7 z$ ] fd 1) H+ E1 ]4 m8 h" T `
set wealth (wealth - metabolism), k5 e. b5 ^4 D7 Y# w, |* A* i
set age (age + 1)
$ ^# c1 t( e" z" Y( j& n4 _ if (age >= life-expectancy)! z1 d0 x1 E% |1 ^; E) K( `! @7 \
[ set-initial-turtle-vars-age ]
2 |9 U6 W( m8 k if (wealth < 0)) C; S# P: ]2 Y& F' P
[ set-initial-turtle-vars-wealth ]: q/ j# b7 V: O* Z2 E
$ ?* o8 O2 Q: q, _2 ~, G) bend$ \6 z1 R2 Z5 Q% ~, Q, T
% \7 e( L8 y' i0 B+ p0 e
" k5 ?" k- F$ H& k" W; c/ L6 N1 Yto setup-plots
& Y/ _( [& W# f4 B+ }; j- p$ P set-current-plot "Class Plot"
4 ?9 ?3 M* P9 A set-plot-y-range 0 num-people
- O4 p5 E4 x+ [0 W set-current-plot "Class Histogram"
+ a( P4 ?) f7 Q7 a. i& u set-plot-y-range 0 num-people' ~& n: T8 S( T" K
end) A3 w" Q& x% z5 y) D+ w# V% `
$ V8 Y. T* s& y( {7 K3 j
to update-plots2 p/ C" z2 R+ O. [5 K# W! a
update-class-plot. F) w5 m( Z- L" f# P+ w+ B3 @! U
update-class-histogram6 R5 j: W. F$ Q+ J
update-lorenz-and-gini-plots
* g, g5 v' S% S( H8 T$ ^end
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5 d5 R) I0 q; V# M+ Ato update-class-plot0 y% w) o1 z5 N* d
set-current-plot "Class Plot"
9 f# q4 I" |5 s4 M set-current-plot-pen "low"8 `# {! @6 E0 C2 m& l: z
plot count turtles with [color = red]' ~0 u/ s! @, l, K
set-current-plot-pen "mid"
/ u8 U# f6 B6 |& C plot count turtles with [color = yellow]
; o, d' V( o- n8 m6 y2 t9 W+ { set-current-plot-pen "up"% }, G" f$ f! X. E/ ^0 l0 _- z( j
plot count turtles with [color = green]$ A* Q u: a! J+ V! A
end
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# {; Q8 [. W2 v% E1 Y/ ~5 tto update-class-histogram
/ I% a5 B5 z3 U set-current-plot "Class Histogram"
8 u5 l( G- y G plot-pen-reset
$ v- e9 t- u- z1 O ?' I& X set-plot-pen-color red4 x" \6 a8 H t4 s' m% u
plot count turtles with [color = red]
; f4 V7 t# _/ t set-plot-pen-color yellow
& w- u Q) }6 \1 w, e plot count turtles with [color = yellow]! a' }0 L% b% v P( ?) D
set-plot-pen-color green. r; _. x5 J4 c9 ~1 J* g* ]
plot count turtles with [color = green]
$ j* N3 O( _3 i3 Z' T2 ]end B8 W$ S6 h: H8 S' O5 d! Z6 T K6 ~
to update-lorenz-and-gini-plots
- C" \ F) M& s set-current-plot "Lorenz Curve"9 a N5 o% ?; ~/ [* V0 f, X
clear-plot
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set-current-plot-pen "equal"$ q- g5 v& A- Q' o: j6 j
plot 0
( W {+ D0 o- {- a9 u4 w d plot 100
2 `7 }$ v; z; q
- Q; C% {; z6 N* x% H/ | set-current-plot-pen "lorenz"4 A8 A1 Z! b2 S) a+ w0 H6 ~9 N
set-plot-pen-interval 100 / num-people/ H* w2 `: N8 L* ]; C8 k; o1 D+ ]
plot 0
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let sorted-wealths sort [wealth] of turtles& r& K M. c6 d8 E
let total-wealth sum sorted-wealths2 p( p5 y9 }+ f. v5 a3 S
let wealth-sum-so-far 0' g; H/ Y" _) v, F
let index 0
g0 s1 s( r/ d3 m. _& k( i; v: M let gini-index-reserve 0
. B |. @8 i$ Z' E3 B
4 `# C: d4 j# y* _1 N+ P repeat num-people [9 v ~/ P' z/ h0 l+ y9 m
set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)" l( f' P4 ^1 c" l! p9 D
plot (wealth-sum-so-far / total-wealth) * 1002 f) Z: e/ d$ U7 k
set index (index + 1)
" i7 j7 q% n7 r set gini-index-reserve
?- z0 i3 T. x( ^+ C' M gini-index-reserve +
. f. o9 c4 D+ ]" ~- ? (index / num-people) -
! | E5 L7 E' S% P7 M, C6 Y( L2 S (wealth-sum-so-far / total-wealth)
! f+ K9 o, A# J0 ?% _( H ]
& g0 P& B, z6 a" Y% e, C W5 R3 e- U' `/ ]& }+ j( m( M* M
set-current-plot "Gini-Index v. Time"4 R% v5 x: r* h
plot (gini-index-reserve / num-people) / area-of-equality-triangle
( o" g+ P! h% u! t1 ?end
$ h. y' X q6 oto-report area-of-equality-triangle3 w; c8 p; o+ {
report (num-people * (num-people - 1) / 2) / (num-people ^ 2)" ^* K, \- `! ?' L: K5 Q
end |