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" d' W9 Q' y g b, n3 U! l
globals
8 |: l2 A2 g7 I- q[, R0 D l/ l w7 ]1 g
max-grain ) w# t& e0 A) n& n. d
% i) K1 ?' ?- U1 U]
' E- u3 j5 z3 ~, ]
1 E! \: _$ |, \3 F! z& Fpatches-own
' d( M" m) O; Z* y& H[
& J2 Z/ {4 I1 n2 u9 E1 U# L grain-here & l8 D( g8 ~, w& G# o$ S2 Z: ^
max-grain-here ; v8 {; ~5 o! S& K
]( {5 f- F8 T$ x. S, X x1 P0 a; h
6 k6 O+ Z2 x! h3 N9 H, d! gturtles-own' Z; c% [' u: u# F+ t
[
4 a& m3 F# Y3 k1 E age
- l, p7 l0 }( c# f/ j7 _: r wealth
. A7 s2 z+ _+ r; T2 j5 g life-expectancy 4 e/ k, n! z8 x% M e6 |# E5 @
metabolism . E0 F9 y2 Z; i6 `6 [6 d
vision
- v' G+ x5 r: ]) z7 M; T inherited + z& t( }' C1 \6 j* J- Y8 c
]
6 w# a9 @: k; x' ]
4 q9 o& W4 a+ ^; e. O' _" F P8 ^9 I4 d, [. E: M* T2 O- W! v: O0 [7 M# F
to setup
! Z. M0 E7 @' C# v ca7 K( Y( e$ A s7 K% m0 m; T% ~3 b
set max-grain 50
9 C0 R% N7 a1 c1 w5 n7 K setup-patches
( x, H( e9 K4 Q6 c: h1 g+ T setup-turtles
- P9 J7 s, `5 r+ H& c; W setup-plots
' ~' j: p3 g* `! ^3 P" z% M update-plots
" f: A I& R0 Fend# `7 j. W+ c z5 L# i1 m0 Z! y
to setup-patches
# z7 m) }3 r# M9 a! ~ ask patches
5 ~9 ?# d, m; y [ set max-grain-here 0
8 \% X1 E; D+ w1 g0 V _ if (random-float 100.0) <= percent-best-land- y# O1 Z' j7 {- u% J
[ set max-grain-here max-grain
6 L' I% s9 Y+ a9 I# G8 ~: [1 e set grain-here max-grain-here ] ]
4 b: K8 ]3 M! @0 x$ w repeat 5" i, R# d3 p7 G" P9 s) f
[ ask patches with [max-grain-here != 0]
, |+ |2 x" M+ {. b4 y/ q( Q [ set grain-here max-grain-here ]0 V1 B6 j9 f9 _! Q
diffuse grain-here 0.5 ]
9 R$ p- ?# A3 H/ J, O" p repeat 10% ]; i) L2 [( A3 H7 @
[ diffuse grain-here 0.5] # L9 b! e9 T, i9 k( c
ask patches
8 m' i. e- I# u$ C3 e [ set grain-here floor grain-here * Z# B* d3 B' B" }* G0 O
set max-grain-here grain-here
" w) t* z# }5 E recolor-patch ]+ [0 K- ^4 r6 x5 y) Y) n/ v V
end4 x( c4 ]( ]9 X; }( g2 | |
to recolor-patch
! i: U3 N" x0 d1 g" P! d X set pcolor scale-color sky grain-here 0 max-grain
8 p" b2 R6 _: Z) W3 v7 Mend
1 W" u7 R) O% l; n5 {to setup-turtles# V6 A c W. ]9 s3 H/ U9 v
set-default-shape turtles "person"
/ {+ p9 T* H6 h5 k( ~ crt num-people5 X# w( Z( M1 j8 `" ~7 r( ^
[ move-to one-of patches
, ?' A) _& |9 k+ J5 N( \ set size 1.5 6 ^! Z; E1 ^; B$ p6 V/ J2 W1 R
set-initial-turtle-vars-age1 F- c4 R4 O: H3 W
set-initial-turtle-vars-wealth
4 i: w% _' ]: M2 v& O; Q9 j set age random life-expectancy ]
4 ?( j' X* a% A0 z8 Z recolor-turtles$ \4 E2 W) L: ]) B ]
end7 g) J5 U' U! L+ Q$ d4 `& F
, d, g$ V) E4 d8 n q* s
to set-initial-turtle-vars-age
! d: U+ E2 }+ \) j% C let max-wealth max [wealth] of turtles% W- o3 ?- _( Z e4 r
1 q ^ `& O1 G" r1 M, ^7 z ifelse (wealth <= max-wealth / 3)
# D6 A8 @& w, `: S. R [ set color red
2 S( b% Q* X6 ]# C0 t set age 0
& ^2 r/ i4 E2 g4 }5 X6 ` n face one-of neighbors4 5 G5 G5 ?$ `4 k) b
set life-expectancy life-expectancy-min +
% K { O) Y0 R0 Z random life-expectancy-max
" X+ ^* Z5 S, ~. o1 p) v set metabolism random 1 + metabolism-low. L+ M, |0 c, B
set wealth metabolism + random 30
7 _- S* ^4 w: @ C& e+ U+ _# w set vision 1 + random max-vision: H% y5 Y0 G8 b+ \+ h3 c* W
set wealth wealth + Wealth-inherited-low ]+ {5 d J. j2 f4 W" ]2 b9 h
[ ifelse (wealth <= (max-wealth * 2 / 3))5 M7 Y( V; d# X4 e. X% c& e
[ set color yellow
5 [6 Y" O, U! f0 q$ G8 q set age 0
# _3 v5 i) a" c face one-of neighbors4 / x; {! K7 t# w+ ^4 M' v$ \$ H
set life-expectancy life-expectancy-min +
# u2 |7 S- m5 h9 y; C" w random life-expectancy-max + 1
7 \4 a, d+ I& D; h set metabolism 1 + random metabolism-mid
) x3 ~& L7 e" K3 ^+ | set wealth metabolism + random 305 P: E# I- Y- X. | i
set vision 3 + random max-vision
, x' x Z+ b- n0 _. o2 V set wealth wealth + Wealth-inherited-mid]6 t3 Y7 t% Q0 i# j3 \5 n
[ set color green
. ]( z5 @2 B1 ~! b) I8 n+ B0 { set age 0
& y1 N# S) _+ B: z face one-of neighbors4
7 R! `" s8 i5 Y* y set life-expectancy life-expectancy-min +
/ S2 F3 R1 ~+ V, w4 _" r random life-expectancy-max + 2: q! o3 g- g; ?5 Z" R/ p
set metabolism 2 + random metabolism-up# a }$ j! N" b0 h# b
set wealth metabolism + random 307 o8 K9 f+ n/ j4 i
set vision 3 + random max-vision
# m# d- ^% k T( ^+ K& F set wealth wealth + Wealth-inherited-up ] ]
% p( j& F! m+ b
& B3 E+ _0 k6 Yend
' ^% q, t: A# lto set-initial-turtle-vars-wealth
i' C& S. X* v let max-wealth max [wealth] of turtles
7 T' y5 h: C; f, V set age 0
% \3 U- }! F1 \ face one-of neighbors4
# J9 n& L% H/ T- _; } set life-expectancy life-expectancy-min +! g" x5 u; L5 l. v3 ^$ H
random life-expectancy-max
7 l& i1 {1 }% N" Y3 [ set metabolism 1 + random metabolism-up
) P6 d! @0 K T: a8 q set wealth metabolism + random 30
3 h$ _" u( I0 V set vision 1 + random max-vision 2 i- V; Q5 P1 C4 O7 @. ~
end
, ~2 S$ C: ~. t8 r3 P9 x/ P( p1 O2 Tto redistribution
) w. L7 d6 x( S0 o/ tlet max-wealth max [wealth] of turtles3 _- ?& J5 u& @3 F$ k( ^1 P2 _
let min-wealth min [wealth] of turtles
. N: M T g2 X6 e! y" }+ wif (wealth <= max-wealth / 3)5 F& m0 Q# I( a
[set wealth wealth + Low-income-protection ]
' q7 J( h5 O& B3 @+ b; nend
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to recolor-turtles# h/ K& n8 q/ y- K
let max-wealth max [wealth] of turtles$ U' G# Y5 X0 I/ H* \% J- {
ask turtles
; Z% J( W# _3 u- e. ~ [ ifelse (wealth <= max-wealth / 3)
" `, [0 f. C% s, W [ set color red ]2 S) {: B1 S- U8 U+ p
[ ifelse (wealth <= (max-wealth * 2 / 3))4 o9 N( T4 b8 h" d% j% {
[ set color yellow ]
+ C( j8 T9 f: l' _( K [ set color green ] ] ]3 N, ]" S8 X8 ~9 G
ask turtles [ifelse show-wealth?
0 r) k# g7 A3 K' ~& T& B [ set label wealth ]
7 B4 a+ V( R$ A5 \$ C [ set label "" ]]
p# G- {' x7 C* lend
% Y, {+ X& [& ?/ e# C$ f% x4 B& O3 p. I
to go; l0 g1 O h+ Y. P: ?8 _
ask turtles
8 a( v) H# F' o/ I [ turn-towards-grain ] / d7 A) [. x, n
harvest- M& ]3 _# v/ p0 \- J0 [2 Y
ask turtles
( d; S" h- k. S' S3 L" s [ move-eat-age-die ]
6 g8 @7 r" t' ?! S8 b4 U recolor-turtles7 X+ i, \& j k$ O, u6 k* W
if ticks mod grain-growth-interval = 0! p: ^8 x# ~" N$ x) M1 S3 V
[ ask patches [ grow-grain ] ]* S9 U7 C, o% O o
( Q4 F$ Z8 A0 A' R) {3 X
if ticks mod 11 = 00 @2 ?- m; r: S/ @" R. A8 w7 c
[ask turtles
( v* {6 {- a; ~# D [ redistribution ]]
/ }- w( \4 L& I/ o" [3 \6 Q% d if ticks mod 5 = 0
. H8 u+ S3 P& W8 T. \3 ^3 _$ V [ask turtles5 g( |7 T( y4 o
[ visions ]]0 x6 ~' j2 s3 A6 W/ c9 U
tick
, w6 v. w# G' E3 t. ]2 C! X update-plots. h& w5 i0 u: X E
end% O5 p* p" i7 ?3 j7 h# U# |
to visions
$ m$ o9 _- A2 o7 V' u set vision vision + 1 " Y/ G- x. j$ a
end
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5 P5 q! D8 Z% f3 a! I( \
' X3 k6 j. i" h0 C, Bto turn-towards-grain " t. X* l T5 G6 v0 D. {4 N3 n
set heading 0
3 }2 Z0 f V6 y" t- H, s let best-direction 0
0 Y2 T0 R. q* I" b let best-amount grain-ahead" j! y/ g$ B8 R
set heading 90
( |& u: _7 V$ q: f5 l* A7 d if (grain-ahead > best-amount)! h# u: C0 ]7 I7 ~. E7 M* u# ]
[ set best-direction 90% w' V; f4 W& C& c
set best-amount grain-ahead ]
* F+ C3 Z0 d$ y4 o5 x4 E) r4 m set heading 180
' k9 S+ x$ t$ z# Y if (grain-ahead > best-amount)
# H6 H' r; C* N [ set best-direction 180/ H& p! j7 Y) n* h% t: M
set best-amount grain-ahead ]
* h$ \! j C/ A' z! X7 p set heading 270) _& e' q h% n! C
if (grain-ahead > best-amount)
0 I3 @0 P2 d) N# E/ G% M% B5 A7 F- [ [ set best-direction 270
" D9 U' x3 w* R8 Z- ? set best-amount grain-ahead ]
9 _1 z% V: F6 T set heading best-direction
- q" ~; E" d& q, |- K7 y9 Mend. m% r5 ]4 E/ D! f& ?
: }/ z& J: O7 b: M( u6 E6 ?
& Q! M0 _! B, L: o1 V; x0 B' t# ^. f9 Xto-report grain-ahead * l: L2 S5 Q2 ^, a+ E% o0 e
let total 0
1 G' ]: q Q1 k0 J' j! t7 Q let how-far 1# _0 @& B; p# Q' J! h. u2 E3 |! f! i
repeat vision& H" F3 j" l# ^+ W# E
[ set total total + [grain-here] of patch-ahead how-far
. E5 \! F! \. o. n2 h8 m set how-far how-far + 1 ]
# O* G, G0 m" o/ S. Z$ c report total9 n5 L6 t" E0 @2 X) p& [
end
( g& h0 F/ c a+ @' @+ x X
( O% @2 b* o y$ Eto grow-grain
: ^' `4 X$ R' s# g! k9 Q if (grain-here < max-grain-here)
, K. l1 v0 n8 L! V0 P* _ [ set grain-here grain-here + num-grain-grown) e1 z/ M" S; h* Y. E
if (grain-here > max-grain-here) " ^ b! w3 D; V$ Q$ Q* S$ L
[ set grain-here max-grain-here ]% \( j/ h5 @+ r* {5 J
recolor-patch ]
, J( C/ o) |& V- t2 P) O/ dend
- Z2 |5 V! b9 n, c' u) c( i, Cto harvest
v1 J9 d9 L7 S1 F2 f6 X X ask turtles1 C, N8 h, k$ b/ l1 m% Y
[ set wealth floor (wealth + (grain-here / (count turtles-here))) ]' i- _9 M2 N5 Y8 Z8 Q n
ask turtles
* L3 S; Z3 C# A [ set grain-here 0
4 T$ F' S7 {$ T b7 S! F+ L2 \ recolor-patch ]% W8 i; @2 P( l) Q1 t4 C
! D# d2 c; H. h! o
end
/ { F" d! \& W' \; K3 S# W$ [" Q, F( P
to move-eat-age-die $ N% S7 b/ f& Z. U3 J
fd 1. r4 F, A. k1 G4 s) U+ C
set wealth (wealth - metabolism)
# U3 f+ W! s! K% a7 ?% [; k set age (age + 1)& ^6 m& i) g* n; J- ~
if (age >= life-expectancy)) V5 o1 n5 B2 X
[ set-initial-turtle-vars-age ]2 L* j( ]. b8 y3 }( Y! c; P6 p
if (wealth < 0)
9 y* k9 \4 S4 M5 k [ set-initial-turtle-vars-wealth ]
; Q6 Y8 W" W. X 1 v" y7 q/ D* d) O" s
end
* V+ ^. |3 P7 k4 a; ~6 D1 q$ A
' M* G) m* t1 I" w: u) a% ]* G
4 h, y' f# L V% Dto setup-plots$ a9 n) u) M! J" G) h
set-current-plot "Class Plot"
% B. T* G4 K2 P set-plot-y-range 0 num-people* R* {4 K% k4 H6 C t3 M) h
set-current-plot "Class Histogram"
% h- y2 E- ^' J9 v set-plot-y-range 0 num-people1 ]& w& r5 b# Y7 n
end
) O/ h3 V/ ?, `4 {2 n, v- y
, p$ i2 A9 i( j1 ~! I# a6 G4 X( Ito update-plots
1 n# @( N4 v5 ^! v1 M update-class-plot) I3 [6 ]7 e. X& O0 V
update-class-histogram
2 Q* C) ~- B) _# x/ [% ~ update-lorenz-and-gini-plots0 e$ K$ B: x: P) ]& Q" M
end, T, j+ r0 L, d7 G+ W. c
) p- \1 |; t# z
to update-class-plot, ]- l0 Q0 O8 e7 h, e
set-current-plot "Class Plot"0 r3 T- X9 J$ r8 {7 k. k
set-current-plot-pen "low"
; F, O/ ~' j7 t0 f( u# s plot count turtles with [color = red]9 o6 ~6 m# H S' O
set-current-plot-pen "mid"
7 |) D# r8 E3 q \% ] plot count turtles with [color = yellow]9 `. Y* d2 U U$ t, }" i
set-current-plot-pen "up"
3 ~, P1 L' i q5 K plot count turtles with [color = green]
3 w, G9 ]) v% T7 Q- v5 zend
( G1 j8 s+ @- n l$ g' n7 @0 }& m6 r$ X8 H* h4 {7 `
to update-class-histogram
0 V! h) }1 Y9 i3 d set-current-plot "Class Histogram"1 _. _" i8 I0 H0 [6 F
plot-pen-reset
6 z* z) n4 w2 G3 i set-plot-pen-color red
6 K+ J! z+ _/ V+ _! O plot count turtles with [color = red]
. n7 |3 R4 a% t. _ g! Q set-plot-pen-color yellow
* }" p' r. `! n: o) q- j plot count turtles with [color = yellow]
. Q8 d, P2 U, I; b; [9 u% V set-plot-pen-color green/ v2 \9 ^+ G- U
plot count turtles with [color = green]. g- U: v9 s$ d
end( n) u% t, `- U4 K/ M2 S, M
to update-lorenz-and-gini-plots
: i/ Y( F: p8 v `7 u2 r9 Q% v( s set-current-plot "Lorenz Curve"9 P* u% v5 J7 F; v9 _' e
clear-plot( A' e Z9 r0 r4 i3 `
0 h( y6 h7 X6 {/ |/ s
set-current-plot-pen "equal"6 i# a& f2 Z* n) X- r5 f
plot 0+ g2 U; t% _7 {, a- `8 v6 ]
plot 100$ c6 t; z. ?- g/ L7 i. z6 I# P2 h
& m) ~4 ` r. }& e! d set-current-plot-pen "lorenz"3 `% {( K. B& }( p! Q: l2 J
set-plot-pen-interval 100 / num-people! d: C; w/ ?0 L, ]3 n1 c }
plot 0
# D0 i7 S6 x6 w: U* _9 a7 w# T( w$ v) J
; E0 _3 r+ b/ v! l2 s let sorted-wealths sort [wealth] of turtles0 j$ I8 ^9 t, C/ ^; @4 @
let total-wealth sum sorted-wealths
$ E# t. G3 }6 B: K* @- o9 V1 r let wealth-sum-so-far 0
! o6 [: }( v$ `) S% t" e2 W% f1 N& b let index 0& R6 k5 T6 _9 `: ^9 \" h' Z
let gini-index-reserve 0
3 C8 \+ ~0 W: y' r' p) }2 b5 p$ t3 l: F
repeat num-people [
+ @7 e, j$ a6 J* M6 z set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)$ J5 x# {7 d/ K+ M9 Z. m
plot (wealth-sum-so-far / total-wealth) * 1003 n0 D: ?: C4 g& N; Y$ K
set index (index + 1)8 \( F$ E% l" N: t3 }
set gini-index-reserve$ {4 D( }/ n9 I7 b
gini-index-reserve +- |: h5 S/ f8 A) Q1 ~
(index / num-people) -/ s8 y T, f# G$ j2 s
(wealth-sum-so-far / total-wealth)( D; ?) c1 _+ h' ]# }) A
]2 b7 C3 }1 l8 l3 H9 @& q
- w- f7 C( W4 ~0 r0 ~
set-current-plot "Gini-Index v. Time"6 W* W6 }! n1 \' e4 h3 t( q
plot (gini-index-reserve / num-people) / area-of-equality-triangle+ A; _; z1 T. b0 d/ v' S4 C$ Q
end: S& r' u, V3 b0 f2 D8 H( e
to-report area-of-equality-triangle; _; N n# e2 O" G! g# X* E" U
report (num-people * (num-people - 1) / 2) / (num-people ^ 2)6 {; P: E% ?4 X4 D* U& t t# a( L
end |