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. r a! J' }9 g3 p6 k
globals
9 ?+ B9 v3 M4 ~1 R8 o( t! d[
a3 w3 j' t; P max-grain & F* q8 k( T" F
: ?) r; r8 r0 n]
/ K( g0 {9 {9 ]/ r! c8 {6 u. O& P5 g6 O3 P
patches-own
+ j) @4 u3 e8 W8 W2 ^9 ^) D[
. k$ r# v$ _; ^& N, N- @5 \ grain-here 6 n. q- E* t, `4 i6 e' e# \" f
max-grain-here + x* L% Y; d0 E" S( N
]1 R$ H( {, g5 _3 r" g9 d4 D q
& N. @& `' O) h& E1 F; O; {turtles-own ^+ Z( Y4 v4 C
[! t' o' I X5 m/ m
age
% q! U+ b0 N9 g wealth " f- h9 N% s- S$ [, O8 W- ]7 ^* {, d
life-expectancy
; P9 B; A- F& `8 a2 L$ w" }1 K0 I metabolism % g( Q. j3 O/ j" _( M$ ]2 b
vision/ K/ Q6 A- m2 w
inherited - O4 Z2 y( ~# O+ Z9 S3 B1 U. G5 [
]. K6 q+ M3 m" n+ M |" T
. D! S) v% l5 s% b& F( b+ v5 n, {
to setup
* X, |% i, O9 b e ca
. R5 `+ K5 `' y( F7 P- Q set max-grain 50
. t- U ?7 E, `! d- ~, y. W setup-patches
9 z. B; w5 K+ P# P) C* \ setup-turtles
% _ z% I- d0 f setup-plots
; F* P# R5 h0 L: V9 l& h& N update-plots. z3 e' c- n* z4 c% h
end1 s% P- ]# N. {. G
to setup-patches
& ?( W3 `8 x0 I3 _% X ask patches
0 ~) B) y# u. A0 C [ set max-grain-here 0
# |9 L, w: U8 Y7 w$ f% c5 U& h if (random-float 100.0) <= percent-best-land
1 K: H" P3 B' y [ set max-grain-here max-grain9 X( D' [0 M$ G1 k8 \
set grain-here max-grain-here ] ] K. O i/ g7 d" a3 L9 \* i
repeat 5
- d& X! q I4 n w, u; ~9 h [ ask patches with [max-grain-here != 0]
; E2 }0 \: @; [6 @* E" \* m [ set grain-here max-grain-here ]5 I8 g7 D0 ~7 \0 f& ]) x. T* I
diffuse grain-here 0.5 ]
0 T7 F# ^% M& \6 [, M repeat 10
$ K0 `8 J2 t ~9 }2 B% m9 M [ diffuse grain-here 0.5]
% a. o4 H h+ L; l- T ask patches0 X4 |; M7 f3 ~1 }& T+ M" w7 R
[ set grain-here floor grain-here - x5 U0 l: I# ]2 U6 _ y
set max-grain-here grain-here
4 D% o+ w D" ]2 L recolor-patch ]( M3 b1 L: N# c( y; B) p1 t
end# u1 y6 c- H }
to recolor-patch
/ y! o/ y7 g& L: I set pcolor scale-color sky grain-here 0 max-grain6 B k% s2 b0 B5 u& J8 H
end
; }% @) E0 `/ l s2 L8 @, Wto setup-turtles
& u- o1 E' M m$ g$ q8 k& M set-default-shape turtles "person" E. i6 E0 Z8 r
crt num-people1 s. g5 o/ X+ }1 A. U
[ move-to one-of patches 6 k2 [1 K* K: P" Q0 X8 @
set size 1.5 ' }* {! Y/ J8 z- f# T8 `6 I
set-initial-turtle-vars-age' ?4 H( u1 [% Q- g
set-initial-turtle-vars-wealth
. V7 k. u% L/ ~$ i set age random life-expectancy ] Z3 i7 S# M4 g+ A$ K4 S9 |( G3 j
recolor-turtles; M# k* n" c6 c6 @7 v; ]. \7 U/ O) J
end
( }4 s) r2 s# O2 t/ X. s" w' ^) w+ N
to set-initial-turtle-vars-age* s4 U# o4 y4 e5 J. d
let max-wealth max [wealth] of turtles+ [1 m7 l. \8 B7 P( |, E! `7 d
( n" Z5 G5 Q( c5 }" d$ y
ifelse (wealth <= max-wealth / 3)
I6 j' O) x0 w6 T, X [ set color red
+ m( @7 r- S, Y; Q- X* U set age 0
4 W+ m) C$ |3 O8 j1 z face one-of neighbors4 8 u; G1 x$ I7 z! b" R: ?4 C$ {3 P
set life-expectancy life-expectancy-min +
" w. `4 v' `" s: \( V random life-expectancy-max 4 u: {, U9 v1 n) C0 T5 @, q' j
set metabolism random 1 + metabolism-low% A( K4 b4 k0 M- l( S
set wealth metabolism + random 30) M' E8 h. w+ V3 ^- k
set vision 1 + random max-vision7 y9 y$ b8 R7 R- {: d+ t* u
set wealth wealth + Wealth-inherited-low ]
7 u: T( m" D+ h7 b$ }7 Q [ ifelse (wealth <= (max-wealth * 2 / 3))/ o; b, A2 f7 ~1 \- p
[ set color yellow " `* j4 T* S( m4 d
set age 0" z8 y; q6 A7 l8 D, k$ i8 G
face one-of neighbors4 6 P7 G* ^( e$ x+ h9 a! A8 \& m
set life-expectancy life-expectancy-min +2 O# t8 ?: a9 l* ?$ I
random life-expectancy-max + 1
9 Q1 F6 O4 f; X: Y+ c' h set metabolism 1 + random metabolism-mid
' \! s) P f$ t1 M2 T% b) j* T set wealth metabolism + random 30
! k: o; z/ y) P set vision 3 + random max-vision
: H2 r. R* C5 h# [ set wealth wealth + Wealth-inherited-mid]8 T; Z& {" `( O# o6 y0 G5 F. ?. d( |$ A
[ set color green
3 c/ ?7 D m0 e# C f7 Y set age 0
) e5 P3 l% z8 @( m L& q( { face one-of neighbors4 1 r* b* u' o& O5 L! N" s
set life-expectancy life-expectancy-min +# f8 t4 }' q& ^# |7 A3 w
random life-expectancy-max + 2
/ i7 u' f! {# o: O1 ?6 ^2 ]7 r set metabolism 2 + random metabolism-up6 W+ a5 K* m2 Z' O4 P
set wealth metabolism + random 30
- M8 C' p2 p1 l. a set vision 3 + random max-vision
; H/ c+ N! O! }4 g3 t6 t/ T6 t set wealth wealth + Wealth-inherited-up ] ] & G6 h9 p1 i& b% h: C4 I6 s
0 k z* A) D0 b) Send3 x1 |" |' I% H7 d o9 ^/ l
to set-initial-turtle-vars-wealth
4 z; l/ E! u% G5 x4 f+ W, G let max-wealth max [wealth] of turtles
3 P5 y9 L+ {4 m" W4 B) d set age 0/ @8 ]8 @! F% R/ H2 k9 `! R
face one-of neighbors4
! E) ?4 {& M- G ]" J3 s- H set life-expectancy life-expectancy-min +
6 i1 Y5 O, p, M: M random life-expectancy-max 9 s* `5 D* X5 H$ ^0 l: _, i
set metabolism 1 + random metabolism-up
, ?; g: f8 D: b; l. x set wealth metabolism + random 30; }8 K" f1 X2 b; b- b1 Q3 U
set vision 1 + random max-vision - w r: s& _) t
end. L$ @: i+ f( i; [2 D t+ A
to redistribution1 B6 k1 p9 I9 n! D9 j
let max-wealth max [wealth] of turtles# ?# o# [. m" r0 K
let min-wealth min [wealth] of turtles* b9 |$ W8 m, X
if (wealth <= max-wealth / 3)7 S3 c1 E9 B% Q# I/ {
[set wealth wealth + Low-income-protection ], o1 E0 Y& ~; Z+ x
end
/ v5 O" s' g4 t5 M
6 b9 [' X& G& g* V! y1 f4 F, sto recolor-turtles
6 g$ G' o; E* i5 ]2 o9 _8 r K let max-wealth max [wealth] of turtles
, y/ ~. B# n$ Q# R) m/ i; B ask turtles
% n: J9 [& `: m [ ifelse (wealth <= max-wealth / 3)
" \( Z9 b. w, Y" M8 f2 M) s$ S9 N [ set color red ]! p8 B2 E0 p8 }$ R% O1 \# d& B
[ ifelse (wealth <= (max-wealth * 2 / 3))
: _. p, x/ _# [+ h$ ]) N2 z [ set color yellow ]
% x7 _. N) i. {; \1 H [ set color green ] ] ]
& X$ X% N! A: V3 c4 R ask turtles [ifelse show-wealth?. o3 H: w6 k# B# }- n0 n
[ set label wealth ]$ h1 b8 @, C1 G. z ^( z( J
[ set label "" ]]
7 S8 x* n. c/ [end
6 I1 z# l5 e$ Y2 }' _. P" W4 P* O6 }# X% K, E
to go
X! l$ m% e+ |: | ask turtles
& P% L5 j: K1 l# O1 X8 ?% P [ turn-towards-grain ] & o# ]9 j/ a0 J0 ^( H( h! L! K/ \
harvest
6 l: K% D' K0 F/ X ask turtles
3 i7 X. l* K: @0 y& I: E- c [ move-eat-age-die ]: _# o/ \. }& ?4 j( a) ?
recolor-turtles0 e7 P/ j3 P1 {* A
if ticks mod grain-growth-interval = 0
, w, h5 R0 r6 J6 f, d! G* w& S3 C [ ask patches [ grow-grain ] ]1 S% Y5 j' S$ {) }* E
8 P4 B2 D+ g0 ^+ Y
if ticks mod 11 = 0. a3 _& l6 N* \6 p
[ask turtles/ n& q& N& ~$ r5 s* f; X% `! y
[ redistribution ]]5 u( {6 l* {0 t1 m/ p/ ^
if ticks mod 5 = 0 y3 i8 ^2 W3 \! p: @$ k/ j
[ask turtles" X L1 E* c3 D& {) X" i. `
[ visions ]]
; s; K6 t# H F5 z% ` tick" ~0 J/ t1 h( W \
update-plots
, R. S; _2 j9 n" j& |/ m, Qend
5 X6 |. I" J6 M9 m( D, Z' Nto visions
& \8 i& a' I" D" n8 i. l set vision vision + 1
3 Q9 U' H B/ _9 R1 m4 Dend
, r2 N# V9 L1 {, M! X" g. X9 T4 l" x; {% X3 L+ `
9 d1 O ]& v! {" y0 \3 \& ~/ ?0 v& K9 @" A7 p; l9 B7 }
to turn-towards-grain
4 }3 z y( E' T/ M' \4 A' i# Y- _ set heading 0( X0 t p, V: L4 P" A1 i
let best-direction 00 N9 y0 l. G* Y, j$ w: Y
let best-amount grain-ahead3 F( N( p1 L" F1 t
set heading 90
# J8 G9 a) f0 [% m& Q if (grain-ahead > best-amount). b, P: O, x2 J7 l) `1 C6 a
[ set best-direction 90
# L- c$ \% | g' f* @ set best-amount grain-ahead ]
/ ~+ ~' N( u# }4 ]& F! B7 r0 | set heading 180 [2 j0 I; }% U& m# Z
if (grain-ahead > best-amount)" `1 D+ O v- y$ X+ F2 [! G
[ set best-direction 180& d1 W/ O! C0 [2 _4 f8 P8 q
set best-amount grain-ahead ]
6 V2 s2 M! P4 ?) D' I set heading 270, ^. B8 r1 g2 W2 Z$ n
if (grain-ahead > best-amount)
& p6 S0 }3 U* ^# B+ l. m0 f [ set best-direction 270: s T% H: s6 L- F) u/ y t
set best-amount grain-ahead ]
& _1 a) c$ w6 l2 v! G set heading best-direction
- ^% k; G$ U. \end
9 H$ O$ L6 J2 `
$ p1 l- K* Q$ n/ B9 q$ ^- J& X Q& ]+ W) s- [
to-report grain-ahead 2 a) j+ t- Z1 Q4 i/ l& b: b, C
let total 0
/ ^5 b7 H8 z, m) Y( x+ ]: e/ g6 Q let how-far 1
3 E3 I8 }/ ^6 e" k; Q& X Y8 Y repeat vision
/ ]' \* P3 k$ Y: ]! M! X0 W [ set total total + [grain-here] of patch-ahead how-far7 I& k8 `' ^! U# N8 T
set how-far how-far + 1 ]
1 m0 \! f; j/ }8 H, s% Y& ?; V report total& t% \/ i( i2 A% o- H- e* c
end
3 ^: Y2 }3 n5 ~
1 J3 t/ K7 F& B8 z/ v2 Z. dto grow-grain / Q/ q: j8 m. [- H8 M- ?. _
if (grain-here < max-grain-here)' ^; o* o) k9 G+ C; `
[ set grain-here grain-here + num-grain-grown( p, l9 ~& N. k) Y! j
if (grain-here > max-grain-here)
) i5 C; c+ b1 `. } [ set grain-here max-grain-here ]
+ y7 Z7 w$ O! }3 u recolor-patch ]- G. W1 @) W- C2 \2 L
end: E( D0 c% [5 I+ ~
to harvest V' T7 @4 }' S9 e
ask turtles, E6 q" l# B" ?
[ set wealth floor (wealth + (grain-here / (count turtles-here))) ]- l3 N. [" N% F2 ^, v* ^
ask turtles
/ Z6 T' J$ Q" o. c# E [ set grain-here 0: m M# b$ l: R3 F
recolor-patch ]
1 I9 {6 m I! `( I$ Y/ _9 g% Q2 k
0 R& H: r b: o& Y `3 Lend9 ]) S2 N+ Y. J* F5 I
- ?( K5 V: y/ _# v0 H7 X" X5 Qto move-eat-age-die 0 E7 v" {( M' ~9 n
fd 16 p. C/ a; [! a. o
set wealth (wealth - metabolism), H/ k. H! ?! ^ {; q+ c A
set age (age + 1)
- f4 u2 G' ] B! z' t if (age >= life-expectancy)
% C6 T2 Y7 C* e+ {; v [ set-initial-turtle-vars-age ]
, c& [5 u3 M4 {. n, d if (wealth < 0)" o, Q1 `5 q9 U
[ set-initial-turtle-vars-wealth ]! `( s: j" {/ E. y
# R e9 ]8 X) D: l/ n9 a
end) R2 W1 O& Z; H% @3 V; @
; p& }3 \0 x* `# U$ L
6 U8 d: q# Q1 O3 |6 A! q! }1 cto setup-plots; ~/ t6 Z1 s \ E' n7 T
set-current-plot "Class Plot"
5 k% C5 p6 B! `% ?4 j4 g set-plot-y-range 0 num-people
4 Z0 Z# k- q, | p4 r set-current-plot "Class Histogram"4 H( b: @* x1 _. e" {+ U/ H
set-plot-y-range 0 num-people& ?1 F- X% V$ S
end: n& k8 U, o5 {/ i* h7 g6 T2 k0 c' F: P& X
8 ~1 ~0 X4 e% t2 j: e- C
to update-plots
$ a7 I: _6 l' @/ k update-class-plot! R P/ d2 Y6 s" U9 ?- }! a2 d
update-class-histogram( ]& y, N8 C! Q+ n0 ^ z. G
update-lorenz-and-gini-plots! R( f, j7 F. [3 ^% i+ J
end
# F' {5 W8 P" G6 k* S" a& {, u& ?9 \) J# G
to update-class-plot! o' a( w. l7 ?
set-current-plot "Class Plot"
9 X# e. x4 x* y9 p& O set-current-plot-pen "low"6 R" N4 ` r5 p. U
plot count turtles with [color = red]
$ ^* _. o" O4 ~7 u" q" U" x; X set-current-plot-pen "mid"1 D! P3 f0 N- ~ w" N4 D/ \
plot count turtles with [color = yellow] O2 _5 m9 I) p/ ? U3 \/ L
set-current-plot-pen "up"
- X9 X: ]( p( R4 w& h plot count turtles with [color = green], x7 p! b Z3 a2 l' b3 E+ g
end# k5 s; U2 e8 }
: g4 k* V2 u& S/ ~5 @, X
to update-class-histogram5 ~4 _9 N6 F* S. k5 A! U! ~6 \2 E
set-current-plot "Class Histogram"
6 e) E' w2 q" n9 i2 z plot-pen-reset5 k, P+ k( D4 L/ k! u
set-plot-pen-color red j/ G3 |: [: ?; ^$ e2 i6 b
plot count turtles with [color = red]
. K8 A, b D( u. t set-plot-pen-color yellow
- n" W" L5 J4 |% ?% z, { plot count turtles with [color = yellow]! X- K3 m3 H/ \! ?
set-plot-pen-color green
) L" [5 q: w2 L4 y/ D4 x plot count turtles with [color = green], C7 V, d! K- }5 K9 `
end/ r- ^0 L, J7 O5 X( U4 X+ _
to update-lorenz-and-gini-plots
" B. g. _0 P# ^5 j set-current-plot "Lorenz Curve"
/ L( B" [( C" K. b& p clear-plot
- V; A( E5 J) H7 {1 v( b" Q
6 j3 Y( n* \, { set-current-plot-pen "equal"
* c( P |$ X! m8 ^ D. ` plot 0
8 U1 G: ~- v; p1 ]5 s) J1 i plot 100
5 O$ n. B5 R4 A& e8 g9 t8 M/ w! W' I! x4 N; y$ ] y
set-current-plot-pen "lorenz"
9 B0 H8 ` \7 r$ j5 U @ set-plot-pen-interval 100 / num-people
8 y1 `0 I5 ]6 V) [! D) `4 L9 b plot 0
! f' S: N) K) S6 Q& x, v( E# J4 x, x
let sorted-wealths sort [wealth] of turtles
9 W' n( r0 i ~ h let total-wealth sum sorted-wealths) K& H7 o# ` E- H1 Y; ^! ]& I" e
let wealth-sum-so-far 0' c2 y7 f T }& b! ]+ W
let index 0. s9 ?! I |! X3 [9 R: V7 H* s
let gini-index-reserve 0
+ s2 S& r1 ~8 I) J7 N
5 j' m7 h1 @2 r" o' \% s repeat num-people [8 e8 q& u+ L+ ~$ e: L. E7 f
set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)
* U) ?7 L& X( J7 [& W H: [ plot (wealth-sum-so-far / total-wealth) * 1000 R7 i- C& [) z$ W$ e
set index (index + 1)- u5 Y; [, X8 U+ i3 Y( d5 v
set gini-index-reserve" U1 Z1 s5 x& X5 C
gini-index-reserve +
+ E% n5 D0 j; w& K) L (index / num-people) -! V z5 ~, N& x) t$ ]3 p x7 v
(wealth-sum-so-far / total-wealth)
# s( ` h! O {. j3 O4 Y ]" X V! m' c3 z: W( e/ k0 [9 p$ j
8 h9 h# `; i" I. m+ k' e set-current-plot "Gini-Index v. Time"6 V4 `% P2 B( I( b- ~
plot (gini-index-reserve / num-people) / area-of-equality-triangle/ z J: T+ H8 y4 e! {3 ^2 W: b% ~8 s
end( f8 A% c0 f% J/ [
to-report area-of-equality-triangle
; n* N# Y8 |) {8 `7 A. B; U4 Q report (num-people * (num-people - 1) / 2) / (num-people ^ 2)5 m( V% r6 U: G D' Q
end |