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$ |2 V( V/ _( B9 ~# ^( R, P
globals0 _# D+ B& ~ ?% k T* q0 \
[
" a; _* q3 C9 O# C3 y max-grain
& R7 B( Y' d2 _# K! N* r4 h8 ^, p1 ^0 ^: |9 R
]% x: S# |0 G' A3 |5 g& |0 A
( O# e2 `! g- ^patches-own
7 w2 l9 i2 j) u5 W[
: F. K/ d, W z2 ~, I grain-here / g1 V0 |1 C2 x0 B" A
max-grain-here ; X9 f* k4 t) G ?; q1 ?- O
]( A+ ?5 E1 J4 b6 \
# J B- v a0 u
turtles-own
( x; x+ k; F) r% E; [' G[
# j( f. q6 h {1 x0 }8 O3 }2 p B3 A age
. Q9 r4 L8 F6 S: t( i3 ~8 v wealth 2 K3 w" @/ r. |
life-expectancy 8 n0 P3 {" g! j1 e! M- g) X2 B
metabolism
2 d1 k; u+ ~3 s; l: c vision! R( S0 f. @ n+ p8 }5 ~
inherited
+ x; V' I# X. J( `1 n]$ o: f, Q: d3 b
" j( P1 ~; I [: R0 t% \# C% }
, B+ F) A4 x' N* N/ qto setup
$ I* R( O* s% g- M* h# u ca
+ ?) n+ ]/ U) n. G3 ?0 R set max-grain 509 K$ H g* l" N: i
setup-patches
8 w( a2 i; G; x5 n setup-turtles
7 c: p' ?* u& v |9 y% |2 B setup-plots
; ^. ^6 h( ]- d+ B update-plots
+ I% p. Y, S, @% h$ Cend1 }! v! z- I- _
to setup-patches
" e- ^; u3 w3 q* o5 o% o7 L R4 Q ask patches1 q/ I Q5 S( Q% l' X7 j
[ set max-grain-here 0; R# t8 X' k) s
if (random-float 100.0) <= percent-best-land: q# w$ ~- w3 C, n1 ?6 f
[ set max-grain-here max-grain
& X e( V; k/ b7 Y( E8 q set grain-here max-grain-here ] ]
/ M# c! J# G- C0 O& | repeat 5
3 l1 [6 y& w9 p7 U( [ [ ask patches with [max-grain-here != 0]
4 H9 X" f2 a" Q+ D0 k& Y$ `, i7 Y8 _ [ set grain-here max-grain-here ]
" K# A9 W3 I0 R% b diffuse grain-here 0.5 ]
- U# f* o/ c/ C/ V d0 f$ C repeat 10
+ G4 d% J9 k2 I4 k" G' `8 U0 E [ diffuse grain-here 0.5]
0 p+ }+ t* q+ L! X$ d ask patches
1 c) a4 f) s( K' ~3 a) Y [ set grain-here floor grain-here
* l7 b6 a) I- _) p% f. S set max-grain-here grain-here / g7 P' c( V! L1 Z" w) s4 @2 r2 e
recolor-patch ]
u* S/ y f& Z: L# V m* L% _end" ?( l p! ^5 \
to recolor-patch
/ R7 ^" o4 W; v. M! ?6 V) { set pcolor scale-color sky grain-here 0 max-grain% e3 T- u- w' a# F. ^
end
6 {& E9 E& L) f3 C( f. {to setup-turtles
- T0 ]7 C0 J! z' c* x set-default-shape turtles "person"
( Y$ x, O2 |0 o4 _ crt num-people4 U0 Z, I2 h. H' _$ h
[ move-to one-of patches
1 m2 ^9 ~, p3 Y0 w# @ set size 1.5
t. ^1 B3 a' R- {) u set-initial-turtle-vars-age! E" P6 o7 g2 S O! X' A+ I
set-initial-turtle-vars-wealth
. K1 }' `$ [: ? O9 I' A; A set age random life-expectancy ]! Y# _1 R$ U" N0 l
recolor-turtles3 f% L1 }' F. c1 V+ f7 S
end
7 X! j& |6 C; N, b k9 H2 [' B1 x& W" a+ f3 W& E; V
to set-initial-turtle-vars-age
; |) F: v0 `# p' {' E/ W' M let max-wealth max [wealth] of turtles4 \8 A8 D, I. e) B; a
# }3 F- M- l/ g: O5 h
ifelse (wealth <= max-wealth / 3)
( n/ t. w& q( T/ @6 H6 Z8 h( |; ?" D3 l [ set color red
7 k& ?+ e5 G3 ~# F- f! v4 f0 m$ P9 q set age 0
# ?! i- `& k+ ]$ l! {3 _# ?) w face one-of neighbors4
- t4 n+ |( U8 `3 W) Y }, o set life-expectancy life-expectancy-min +5 O; [) S( [+ j$ F8 Z( {7 M
random life-expectancy-max ; n/ {6 |' T4 u; d
set metabolism random 1 + metabolism-low
( G- S/ l/ G- V: H set wealth metabolism + random 30
4 d3 w" C, B! E6 o7 c; R set vision 1 + random max-vision
; g% ]5 J4 \7 `8 s* J$ I set wealth wealth + Wealth-inherited-low ]1 Q0 B- m& j& S0 n* E: `
[ ifelse (wealth <= (max-wealth * 2 / 3)): {3 N- @/ c* X! t0 g0 {" c
[ set color yellow
; s& ?7 \# y0 |1 I4 V7 \/ _) a6 z set age 0 L# f! A8 n6 E, J$ n
face one-of neighbors4
3 B/ d' \% i7 ]3 ~ set life-expectancy life-expectancy-min +
$ P( ~% N! |8 O random life-expectancy-max + 1; W8 I* i# n8 p$ g( `8 E
set metabolism 1 + random metabolism-mid2 o/ B' D1 V9 ^ E! D/ D5 v* {
set wealth metabolism + random 30
: f- X- s9 P' g# g9 l/ ]* l9 U' M, { set vision 3 + random max-vision( ?% E4 z9 o6 |! {
set wealth wealth + Wealth-inherited-mid]
- t4 n3 P8 A/ E- K% B% | [ set color green
# c! @ ^0 b! Z' e set age 0
8 T0 }" g) N) a0 z, a* I& I- b8 ~ face one-of neighbors4 # i; C4 L/ U7 V/ J! S
set life-expectancy life-expectancy-min +
, J8 {) }/ T! P random life-expectancy-max + 23 ~8 d8 J' w: E, y( y
set metabolism 2 + random metabolism-up
( t) D6 E, C1 S! b1 \% } set wealth metabolism + random 30
7 H( l! g5 I1 l6 C$ N6 j$ o* Q set vision 3 + random max-vision3 ?/ Q/ {/ w# j: w9 }* e( j
set wealth wealth + Wealth-inherited-up ] ] 6 Q; L/ }0 w( E. S
0 s8 w6 ~8 b0 b; P
end h* |" |9 @( x! @2 j
to set-initial-turtle-vars-wealth7 B' i5 {- x8 ^# S4 T, j
let max-wealth max [wealth] of turtles
) B7 W% I% ?0 l! e/ M set age 0" D2 i: K k: c- a
face one-of neighbors4 + ]: P8 S) F1 I1 k4 j$ T
set life-expectancy life-expectancy-min +
, l% v6 G0 I q) D. q9 v; Y random life-expectancy-max
# T+ O2 ^( `( R/ w+ g) ?* V g" m set metabolism 1 + random metabolism-up* g B0 I) v$ h% T) E* \
set wealth metabolism + random 30, g% M& J" ~* q: R. V
set vision 1 + random max-vision ) l0 `2 q9 ^! _7 L
end
* j, i( [2 S: lto redistribution
( _* k6 c) k% I. X/ i' I) a* V! Flet max-wealth max [wealth] of turtles
0 n0 z4 [" H; i, alet min-wealth min [wealth] of turtles) l( ]6 z* j; `; Y7 L4 m
if (wealth <= max-wealth / 3)
* [' {" B! O" A% j( c [set wealth wealth + Low-income-protection ], U' U5 N- ?% g6 w/ ^ a, e- [
end
4 W+ J: w; h3 o' P' w
) N: U# t+ f! [( \1 `to recolor-turtles
3 e6 \1 C6 ]2 @5 Z# U let max-wealth max [wealth] of turtles4 [& h1 _! p* I3 }9 W$ D* g
ask turtles8 V: K8 g6 i' r2 j5 a/ a9 _1 e
[ ifelse (wealth <= max-wealth / 3)$ D2 p1 _5 `7 V9 }
[ set color red ]
' g; S$ e3 \" Z3 P9 h [ ifelse (wealth <= (max-wealth * 2 / 3))6 w* m- [+ ^9 B1 m
[ set color yellow ]/ L% O8 ]3 F, w3 G! F
[ set color green ] ] ]1 F9 s0 A1 i# H2 x% {7 T* e
ask turtles [ifelse show-wealth?
. q2 ^1 ~' b+ Y5 b3 Y [ set label wealth ]
8 z. R1 U6 O% ]+ D0 D5 e [ set label "" ]]
: s/ c! R; F: ~; `; D3 Oend
& _7 l6 F9 z3 {3 i* k5 W
, ^; S# j% f( j" K& g8 nto go* l5 _. E% a$ E% A4 f
ask turtles
8 E0 G. C- w6 C1 I+ x [ turn-towards-grain ]
; K1 R0 o7 M0 |' r! ?3 U+ c( Z harvest! c# |. l5 V/ C1 U
ask turtles0 g3 t A- `7 x/ q6 P+ X% b" X: _
[ move-eat-age-die ]" T. T, N1 |; n @% B4 S6 H
recolor-turtles% m, G: w! Q( B$ `+ |; a9 [
if ticks mod grain-growth-interval = 0
+ M8 W7 m* [. p [ ask patches [ grow-grain ] ]1 V: S8 D" b* _0 W4 x2 n
$ M9 I( G9 J$ x& z' ] if ticks mod 11 = 0: M( W$ b4 p U+ f: v6 ] `# t
[ask turtles* m+ f( j$ a* W2 o! m# C O
[ redistribution ]]2 L. k: C' X& e0 D6 W
if ticks mod 5 = 0
$ s+ ^1 z& S2 g% P# [1 ~. m [ask turtles
; j/ R- U3 n( A. p5 k8 G5 \ [ visions ]]
- d; p, r) [& e& }) O( X tick# f: J% \8 H8 Y* o! L* ~5 r
update-plots1 Q3 H& q" \) ?0 G7 n3 s4 w( M/ f
end/ v1 @1 ^9 N' e
to visions
l& y) l" D4 J4 B6 @! ?, s set vision vision + 1 ) `1 z9 z& N2 s& L
end
) m! w8 d& m! I! R" i0 V& J' R' V( A2 G: {, i, }, X" `7 |/ y! e
/ A# U8 k2 D1 E) n! A
; g/ ?9 s1 C( A" R7 Kto turn-towards-grain
! w+ V/ I( C7 K& N9 e% V; k set heading 0
1 K* h6 d: W3 m let best-direction 0
2 `* h1 F6 L% ]5 g* C t2 \ let best-amount grain-ahead
5 K5 Z; ~% Y: `+ j% M set heading 90: \+ K' } R1 Y/ w
if (grain-ahead > best-amount)% v @7 n( d1 Z+ W( z$ g- R
[ set best-direction 904 c7 c1 T( h9 |1 {) V: e# \6 H
set best-amount grain-ahead ]
& b, p1 [. I, G9 l. X set heading 180
( K6 r. [ b, [) f$ Y; O! A if (grain-ahead > best-amount)) l4 f" V! M% }# s; X4 J1 j& W
[ set best-direction 180 ?' M- Z8 b; r, B
set best-amount grain-ahead ]
( ]; f6 J `2 ?6 f set heading 270& d% ?; l' N. I+ d
if (grain-ahead > best-amount)
: {1 c& d+ F1 F7 P7 o [ set best-direction 270
" {5 K6 k3 y. b1 e8 h7 W set best-amount grain-ahead ]" x7 K$ \9 t9 X7 _. X. Z
set heading best-direction; B0 x( @9 J5 ~* Z& A
end- `8 ]/ O4 j) G" x3 P
1 p4 O; S! C7 m
* o. W a# F( X3 C+ T9 h" N6 `) H
to-report grain-ahead
+ x! l) \ X5 n let total 0 g- R& o- f6 y- k3 y# e8 C
let how-far 1! { J7 @8 b5 f) A3 m) o9 ?
repeat vision. ?, M2 i& d( i$ e# j
[ set total total + [grain-here] of patch-ahead how-far( R5 t! V; N$ R$ t8 J- c. |
set how-far how-far + 1 ]' q9 x& t; S% {+ C! O+ r5 v
report total
/ v! l4 Y! q: Z1 i: ?5 ]end
& z n8 c0 O9 c# ~* }
' H$ I. U, Y: ^6 S/ E0 J& e( f. |* Bto grow-grain 2 h5 z6 o0 ?) y; F5 Q2 T( }1 z
if (grain-here < max-grain-here)
9 S6 \) c/ {. N. r" | p+ q2 y2 g [ set grain-here grain-here + num-grain-grown" G% j8 v- V6 d4 r- R+ l
if (grain-here > max-grain-here)
8 S, E' p! S. Y) M1 Q [ set grain-here max-grain-here ]
4 q8 a+ e- d3 L# a P$ e recolor-patch ]6 ]! X) g! [! `7 O T1 O
end
% P/ S$ T! D7 c9 ?to harvest
, o4 ~3 Q' o( l ask turtles
( H% {& u: K8 }$ s' V9 S l- T" B% L [ set wealth floor (wealth + (grain-here / (count turtles-here))) ]7 |' [* s0 w9 ^# o5 [5 I
ask turtles
, x# ]+ s) m0 D/ x [ set grain-here 0
# ~. ^% c# g1 @) s1 f& O" R recolor-patch ]1 p/ e2 Y- F# ?2 @5 T3 h1 c. s
2 U. F9 {) R* g" q4 \" u; Oend
2 T6 `1 n4 S+ o8 H! w+ s
* A; g" t( `* T' |+ i, Lto move-eat-age-die + K4 ~& Z3 s: A
fd 18 }; n, `( F5 }% X4 Y \
set wealth (wealth - metabolism)
' f* c/ R+ [2 N+ j set age (age + 1)
+ k4 ]: ~) k% k: F if (age >= life-expectancy)7 @# Q* T* g; C, _
[ set-initial-turtle-vars-age ]
" q) F6 r5 j" p! h/ u$ F8 L if (wealth < 0)
( l7 h k! w1 O: u' p G8 S1 | [ set-initial-turtle-vars-wealth ]% { l9 K2 ^( X$ y
/ n9 @: x% ^: C# ?end
+ r8 H3 R/ L- t; s7 j3 t. f* _
" K. o- ^. n4 Y& J, z2 \- D" M( ]
' B3 w; e; b# Q( Xto setup-plots5 V6 F% n) m& @& C: z' z
set-current-plot "Class Plot"
# P! u5 o; q& W- e" Z$ B( g6 I3 M% [' ? set-plot-y-range 0 num-people
6 U# M! C& C& C8 s5 \+ h! [ set-current-plot "Class Histogram"
5 ?3 C( r# A+ e0 Y2 w4 G; b1 q* K set-plot-y-range 0 num-people% u: j8 h: D3 b# n' H0 g
end
2 V6 [1 v8 @& }" A! c3 ^8 y; P4 o- }9 P3 q- W
to update-plots4 r8 ~* A- W7 T: r7 _% Q( G
update-class-plot
$ z) J2 G6 \# c' |9 |. o. d update-class-histogram# U+ M& X! Z+ J% C8 r, {4 ]- G
update-lorenz-and-gini-plots
6 k, _" s$ c6 a8 L) ^; ^ Vend+ t: G" {) p% V; l
, k6 T6 y( x4 W( i k$ M
to update-class-plot- p" ^7 J* z0 x7 w
set-current-plot "Class Plot"5 C( [1 o# K3 S3 A- N, ^8 H" O
set-current-plot-pen "low"
1 `! A9 ^( N% O) e6 f h2 B plot count turtles with [color = red]
. }6 R% t4 |5 G( b, z set-current-plot-pen "mid"# p5 h, z% f* V* }: n$ @/ f2 T8 @
plot count turtles with [color = yellow]9 O, T8 g3 g% X
set-current-plot-pen "up"
8 l# h# }) A9 i+ d6 J) q; s plot count turtles with [color = green]5 {: f8 B! V' o- m
end
& U: |$ Y/ e' _
/ A* l- e+ ^) c1 p4 c) `" nto update-class-histogram
0 X0 [2 m. W9 n set-current-plot "Class Histogram"2 ~$ Z: K, Z6 ?! g, Q C0 n, v
plot-pen-reset
0 Z: V# B- ?+ z set-plot-pen-color red
9 i' i. N0 L+ P' x plot count turtles with [color = red]+ |/ O, }; K! ~+ M7 d4 [0 n' R
set-plot-pen-color yellow
- Q8 b5 t% x1 Y E plot count turtles with [color = yellow]5 W" {6 e# H/ A
set-plot-pen-color green
- D6 f6 \6 K) p( p, _0 [$ w3 L plot count turtles with [color = green]
4 Q+ C) m- ~6 u' g* Cend
5 s5 M! F1 H1 _1 E2 ?5 q8 A' @# ato update-lorenz-and-gini-plots. f$ j) _5 z$ N4 ^* H
set-current-plot "Lorenz Curve"
$ f1 T2 O8 m; A clear-plot
0 }- T Q8 {, U- y' u! O
' e K: B' t1 { J, |0 h5 v set-current-plot-pen "equal"
/ K) Z+ T5 K, ]; Y+ G2 { plot 0
7 N" c) X, @8 h0 N( ? plot 100- U/ h6 A1 ~4 `% y. B
2 k5 b' N, S$ p8 f5 m set-current-plot-pen "lorenz"
& ~3 e# n7 ~9 u7 R0 ^/ i: _ set-plot-pen-interval 100 / num-people
2 q3 `& G, b( ~% ^2 a# f8 |9 B plot 02 u0 A* D1 Y/ D7 ?; V/ S" ]
! A6 e' B# q6 E9 E7 _# y: b let sorted-wealths sort [wealth] of turtles
. U: P5 `0 D& P& ~- a+ @ let total-wealth sum sorted-wealths
: u1 I/ V2 i: |2 @ let wealth-sum-so-far 0
, W W/ Q- A7 w5 } let index 05 z% ~# i2 Y3 H# @, {9 W2 w( [ Z* e
let gini-index-reserve 03 S$ A. w1 P! {2 k5 M
/ N9 ^2 u3 c% K/ `( W" ?, x W) E
repeat num-people [
1 `- Y5 c4 y. w7 b7 ~0 { set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)
t2 ]0 O, r& [ plot (wealth-sum-so-far / total-wealth) * 100
`' j4 f/ b$ T& z+ w; v: H set index (index + 1)
) d: D* B- W" e @ set gini-index-reserve
: `5 u$ ~1 u$ L' T6 Z4 M gini-index-reserve +% y- g; F3 E$ o; z" J9 x
(index / num-people) -
4 S1 j5 E8 T+ ?+ \; U5 c- _/ z (wealth-sum-so-far / total-wealth)
1 @$ [: y6 U0 Q6 k- R7 @5 Y# g ]+ f' ^+ f$ [ _. `/ W2 L1 `, y4 @
- I, Q9 _% o( l/ L* o0 I
set-current-plot "Gini-Index v. Time"
4 P0 X. P3 o1 P: m ^$ ^" F. E plot (gini-index-reserve / num-people) / area-of-equality-triangle
/ \' a9 X' |: v& E) C" s2 }; k& i3 Mend
$ J8 G4 n R6 [* S2 N" yto-report area-of-equality-triangle" }9 f. \, p6 W( \5 i" V
report (num-people * (num-people - 1) / 2) / (num-people ^ 2)
/ F- Q s( {" X! z( _1 Eend |