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/ W6 u3 A, w1 o- J3 m! h
globals
1 s6 F- t) @, S[+ U; [2 ]& t C& E w' j+ t
max-grain 0 u6 g: w& {' F+ R/ N6 _! S8 @0 o# ~
6 A% Y* d& I$ w1 m6 D
]0 \0 O; h! y( A& }, a0 f! p
/ x0 ^: p/ g9 ~4 @
patches-own0 `5 e1 K3 [6 U% X
[! H" }& |8 V5 y% V6 v/ `/ p/ A
grain-here
. y/ u3 C" k$ B0 n: M+ f, Y+ Q& p max-grain-here
3 U0 o( G( R7 |6 _: k( ~]& ^, i/ D& Q4 d; w. R0 f' O# B
5 B2 E$ Z* v" n. w! p+ zturtles-own
( J3 ]- D0 |) q! ^' v[
7 `- o5 z$ C4 P5 J age
( m! N# @7 b5 o. s: s+ v Z wealth
" b6 r" R- y: O! u; ^( ^! P life-expectancy
5 ~1 D/ b: A: N& @ metabolism
4 I. n* t) B" i& q. z- E vision) { \& q: l( z5 E- l
inherited ) T- x5 I2 L/ I, Y
], N% l1 H* |; S+ S9 B9 ]' Y8 y& a
% a) j6 \: \ S% v# Z( x5 D6 _- p% y, r& a; `" ?
to setup8 Y0 v# d$ M( `1 g
ca
- k- {4 s' o2 ^1 e set max-grain 50& b0 h1 I( q2 _( k6 s
setup-patches: p9 }" ^: [* u% p( x
setup-turtles
; U& s H8 n( h: T r, C! j, u& q5 S setup-plots
4 J; e- H( H. t! _4 M0 Y6 x update-plots0 i! i h0 K8 k
end; u. D, U2 T/ G. N6 y3 l
to setup-patches+ e6 ^9 O# R: b' ~: N' w/ N. _
ask patches
9 N1 f: i& C& V2 O3 r& ^ [ set max-grain-here 0% H2 Y* m6 p0 X0 g) q2 Q6 m
if (random-float 100.0) <= percent-best-land b: G2 @* `+ @+ m$ P
[ set max-grain-here max-grain. K/ ~ ?5 I' q- \8 Q
set grain-here max-grain-here ] ], J# c0 L: s1 ?0 H/ x' _$ {1 r
repeat 5) \: s/ j8 N9 {
[ ask patches with [max-grain-here != 0]
! [& A* S; ]' H5 j [ set grain-here max-grain-here ]
) {6 u; C2 ]# W$ j; x# M diffuse grain-here 0.5 ]
1 j1 C) m1 a" S' `9 [2 t repeat 10
+ P0 a8 R) O- L7 w- u [ diffuse grain-here 0.5]
+ {, U8 B, T% [ O9 q* b0 M& V1 R" G8 V ask patches
% |! m4 c3 g. i [ set grain-here floor grain-here ; Z, h; ]* w6 ], q6 z& A
set max-grain-here grain-here
( y& {; x; D# w& e4 v n recolor-patch ]+ _& j( O2 C5 Q5 A
end
; K+ I' e0 ?$ I6 G6 \* Y6 Pto recolor-patch
8 ?2 u3 p& ]" H set pcolor scale-color sky grain-here 0 max-grain M% c0 N9 h8 o% D
end
w# K& O+ f3 P+ G# w1 {0 U6 |to setup-turtles* x. m4 O; Q" b# q3 }* V
set-default-shape turtles "person"! {& ^9 S5 X* f& z3 {
crt num-people
& @# Z% }3 |+ @ [ move-to one-of patches ( e3 e, p( i! ~: X( g2 V+ ]! _) ^
set size 1.5
" B! K- Q: G7 W6 P$ B' Q) R set-initial-turtle-vars-age$ h* H$ F& a3 H& t: w$ ]5 d
set-initial-turtle-vars-wealth
7 a) z, l1 L3 B set age random life-expectancy ]
# j5 [6 y) y( |5 ^& P$ ]& p9 W recolor-turtles
, T/ D9 W7 |; q2 [end
; J& s0 c! Q5 W$ y/ P0 ?& m
9 [' X0 S3 t2 _( L7 D/ _to set-initial-turtle-vars-age
5 i$ b0 y& L) w" |+ A let max-wealth max [wealth] of turtles
7 Q% g& M3 q" o/ L) e8 p& J) N ! v6 F$ U- J. Z3 o. T$ W# O9 x7 [; B
ifelse (wealth <= max-wealth / 3)& N$ r% `/ g; u7 `0 M' s) Y9 U
[ set color red
6 V- h7 M5 y, h. u6 G; ? set age 0! W) g% F7 _1 b# b* m
face one-of neighbors4 3 u2 Q; b$ T# }5 o+ M; M5 B2 P
set life-expectancy life-expectancy-min +
3 C" S$ I- i. f: h random life-expectancy-max " E; E! b* O3 A6 q0 T/ i6 i8 d
set metabolism random 1 + metabolism-low2 V+ C. A. k7 S- E
set wealth metabolism + random 30% j1 [- _$ y) c% }% L
set vision 1 + random max-vision* |) p4 E- S' q: t6 S7 f* z
set wealth wealth + Wealth-inherited-low ]
. c* s7 w6 W8 ]; C& ^) X' @+ o [ ifelse (wealth <= (max-wealth * 2 / 3))* m9 |: u! p: P) v5 n5 x& M
[ set color yellow
8 N# ~/ z/ x4 c$ W2 q set age 0
7 d+ x( d+ A4 ^+ ? face one-of neighbors4
! Q7 c& E0 {8 V8 F7 b set life-expectancy life-expectancy-min +
& R, K" b, d/ \% |4 |( ]! p% F+ F random life-expectancy-max + 1
$ X% @& Q, m. p set metabolism 1 + random metabolism-mid
# r8 n' `4 m1 b) _% X# ^* G set wealth metabolism + random 30
) K/ u3 B+ n9 R$ G/ k set vision 3 + random max-vision
, U# I5 x. c8 h0 P o4 Z set wealth wealth + Wealth-inherited-mid]: E% ?$ g& r6 w: j* E L2 b0 b
[ set color green 7 i1 K# |/ h: v/ r
set age 05 A5 z& c B8 m
face one-of neighbors4
/ C" X6 v6 z4 h9 s. F set life-expectancy life-expectancy-min +
! U) p" g- X+ K8 N7 H7 W random life-expectancy-max + 2
s6 N. B! E5 U set metabolism 2 + random metabolism-up. W# L+ F6 Q6 _5 ]: @
set wealth metabolism + random 30& R( d: w' {+ ^7 O/ w" \; A {* z
set vision 3 + random max-vision
. ` n; g: \$ O9 W8 E% q) ] set wealth wealth + Wealth-inherited-up ] ]
' w: J9 g) X5 m9 R, M F
# V3 q% k% S1 i4 t/ d9 o( f0 Y5 Cend% B. f/ `0 w" ^1 j( {8 a
to set-initial-turtle-vars-wealth
: U# H4 Q( m, u3 y- Q let max-wealth max [wealth] of turtles3 ?/ r" }/ T4 y
set age 0
7 _: ~" r# B! F5 Q, `* o face one-of neighbors4 # Y6 \" n I8 e, j$ a
set life-expectancy life-expectancy-min +- L+ k" K( Y4 O$ R- h
random life-expectancy-max
* T& ^5 O& _8 P) E. Y9 E set metabolism 1 + random metabolism-up
4 z* k5 T8 B: O% l J& l& _9 C set wealth metabolism + random 30
" }2 O$ m* d: k set vision 1 + random max-vision - S5 H6 S! g5 X. { E
end' i' v* }" L' a4 {- d
to redistribution' U: s7 t* m7 \+ C1 n5 o: J
let max-wealth max [wealth] of turtles
: R' m. K8 @: E# g# p. Plet min-wealth min [wealth] of turtles
7 V# F6 r4 n/ c( e4 lif (wealth <= max-wealth / 3)
* e3 J+ [* i: O [set wealth wealth + Low-income-protection ]
! {8 N+ i6 O" T$ p- P7 C! Eend; r" P k( R/ L9 a* o0 R4 S0 p7 H
% D% h* @0 V/ b b9 M" j" c* A% Mto recolor-turtles
1 v7 q8 w N0 p% e let max-wealth max [wealth] of turtles
6 p% b+ f z3 {0 a( Z- b0 i ask turtles
8 Z' E: J; \: F j# M [ ifelse (wealth <= max-wealth / 3)
% `' v) @* y4 ^8 s! A* H# x [ set color red ]- C+ H4 C7 P- A; ]: o7 _
[ ifelse (wealth <= (max-wealth * 2 / 3))1 N( b1 i6 c, N" ~5 m+ o( E0 [' Z; k
[ set color yellow ]
5 k5 H: M. ]3 L9 W [ set color green ] ] ]) ^# \: _* S# R* l: Y
ask turtles [ifelse show-wealth?' r3 P w) z5 N, S" @! q
[ set label wealth ]1 `3 T: U( y# U' c/ D1 @. N9 F. e
[ set label "" ]]
# m; {9 b( X) V, v6 X: {5 Zend4 i% X4 O0 P3 f! G3 z! d* M
8 I- L- _: R5 x0 j& }
to go
7 ?5 {- s" I" N1 h8 G6 \- m ask turtles
* G% Y; ~6 d) n& q [ turn-towards-grain ] % }+ Z5 E0 t6 E2 R
harvest
6 X8 S. |- X* `9 g) G2 ~ ask turtles
6 I6 G4 \; r5 e" e+ k [ move-eat-age-die ]: H: n! N- g$ w6 K- e2 V+ b9 A
recolor-turtles
3 y/ Z( h& g; }3 S if ticks mod grain-growth-interval = 0
' V# L7 `6 \0 d6 E6 T [ ask patches [ grow-grain ] ]
5 H1 {& i: C8 W' W1 L) L% ^3 D9 A! c
+ L. o% s* B6 N: @9 `6 B# W if ticks mod 11 = 0
o4 N0 U9 K6 d% O- _ [ask turtles L! }$ u5 A' Q* c/ x9 m- `, G
[ redistribution ]]# F0 W% ^0 A6 L
if ticks mod 5 = 02 Y" f7 ]) b8 s, [
[ask turtles0 D) U" z$ Q$ i7 d* C# G F
[ visions ]]5 L* p" S$ r/ Y0 j
tick1 P! y" A) w, X d
update-plots: Z: b8 O/ T4 Q- e- V8 l
end
" q% V* F; J7 cto visions
- w& d; C: {" } set vision vision + 1 6 H% H: F; @- \% _
end
% X: O% Q- A9 L5 Y. h& F8 P$ z. v
$ g! G6 `2 `. C; }( t. i9 f2 W7 K1 w
' S1 H# i/ h P, @! O) Q9 ]; E& |# i+ i" a9 @8 B( e3 R7 [
to turn-towards-grain * g: t5 p6 l* e: G0 I3 ^% m7 i3 x
set heading 0
% J$ P" O: I8 g' O# z* v let best-direction 0" V/ K- ]; V( R6 S
let best-amount grain-ahead
1 K% d+ g# ?( U6 f8 x- l: j( H" F set heading 907 {8 h0 h6 n1 E6 X+ D: m* x
if (grain-ahead > best-amount)
3 y Z {) M8 ~/ z/ k1 p2 Z [ set best-direction 90* R' Q' X9 {2 [4 N( B
set best-amount grain-ahead ]6 e: k/ R/ ^: h& G8 y0 s' |& k% X' `
set heading 180
7 Z3 T- X! N9 B" D if (grain-ahead > best-amount)+ k: T6 }$ N* A7 V4 r9 z
[ set best-direction 180, Y+ ~! l* ?: s3 E7 H9 ]# f
set best-amount grain-ahead ]+ B! n! N( ` [ j
set heading 270
7 {5 ], j! U# |& H* C) t if (grain-ahead > best-amount)+ b* F' A% _" |' [3 }
[ set best-direction 270
9 I8 t/ e. h( s) ^ set best-amount grain-ahead ]0 W6 Y5 M) ?6 y: a: o
set heading best-direction8 Q- y5 G$ R4 o/ d) {: R# u
end
& f1 s( {0 y) S. k& I" R! S$ G+ G7 I. a- t( q8 n; X
8 m$ f4 A7 p H1 l2 }8 Kto-report grain-ahead
# F& u# z; `; @ let total 0
- Z. B% {+ u5 t! j! K) R let how-far 1
# E @3 z8 S7 M# @% ] repeat vision
/ g7 V2 g. V8 J+ `; t [ set total total + [grain-here] of patch-ahead how-far U/ h r2 K9 r. P. `0 d, v# @$ `
set how-far how-far + 1 ]2 ~) k/ Y6 n* |
report total
% n7 v/ T5 f0 _; ?5 dend% E6 e' p8 y) W9 z4 w. G5 v" a" B6 `
6 s* P& B: o( Z, |7 Xto grow-grain
& O( G. u. Z% p: X. J ? if (grain-here < max-grain-here)4 O s* E$ X ` M. a
[ set grain-here grain-here + num-grain-grown2 ^% F$ t0 p7 j$ I
if (grain-here > max-grain-here) : d7 @2 O& \7 L+ u/ u
[ set grain-here max-grain-here ]1 p2 y+ E' e+ H3 r3 ~$ K
recolor-patch ]+ U' N' I$ Q* L
end
! C" b& n3 R. {( {: K* k' lto harvest
& S( V2 Z. C7 m0 N N/ C K- } ask turtles
4 }2 m, M- H" Z/ R+ Y [ set wealth floor (wealth + (grain-here / (count turtles-here))) ]
) V7 N1 ~9 w1 J, C m# x ask turtles. l4 P" c& Z! D% A, w
[ set grain-here 0
6 G( H9 J2 w& R- c3 Y5 y recolor-patch ]3 p) T1 f: e- o0 j8 U) x& _
9 g+ T$ _6 x' g. @* }6 Uend1 c% G: I3 D4 N- F
6 x# T3 |* P: A, Yto move-eat-age-die
* U/ i Q3 z3 m4 Z4 S fd 1% ?, ^+ h/ l9 d" l
set wealth (wealth - metabolism)
- ^# ~* R6 u) |* n set age (age + 1)/ L$ G4 x% }/ y: Z
if (age >= life-expectancy)
: c* b" l0 N3 ]) X6 | [ set-initial-turtle-vars-age ]
; Q h* [8 m! ~ if (wealth < 0)( T: @& l V1 b5 e, b
[ set-initial-turtle-vars-wealth ]
p$ I; E" _/ c: d7 Y ' \. w+ c- [- _1 \5 x0 I
end- J5 j* L! j5 p; i+ N2 G4 x
0 R2 x. Q8 w6 }- F9 u
% ?+ g4 R, L& W( @( E% D% ato setup-plots
% ? v8 A d8 e$ ~* l% t6 Q set-current-plot "Class Plot"0 n! [7 H( {1 {; \" f. `8 h$ I
set-plot-y-range 0 num-people
+ W0 O! @# Y1 N m set-current-plot "Class Histogram"
8 q+ @4 s* O+ r3 M- y4 B/ L) q2 p set-plot-y-range 0 num-people
`0 Q& W, P, i0 P4 I( V" vend3 g. k F/ c+ ^6 w
3 W4 ^7 E8 X) |8 P3 J4 Dto update-plots
! ?! v, P' m! l# b/ \& q6 ?2 Z update-class-plot" [6 `+ G6 D3 g- s; ~
update-class-histogram! h1 q3 k. z- r+ u, u1 |" i
update-lorenz-and-gini-plots
& r" h, R \" l; n0 ~! ?5 \5 wend
L, e7 N3 U/ U) y1 C% @8 T6 @; R0 j; j% @( Y, _% r. o
to update-class-plot
8 n- s+ l' q0 x! H set-current-plot "Class Plot"
5 Q: y& f8 p7 N set-current-plot-pen "low"0 \% j, C3 M: @7 f+ l }
plot count turtles with [color = red]2 H+ O$ \9 U; U! g; B! B6 C
set-current-plot-pen "mid"% s- n" `4 g: z4 t! k" E
plot count turtles with [color = yellow]
* s9 c. @2 f! ?4 \" ] set-current-plot-pen "up"
/ c! ~ }- l3 g+ d plot count turtles with [color = green]9 P1 M& t: L4 M& q
end
; Z8 V V+ r1 I8 q' K- C7 ~) b5 u2 e* Q9 _$ T; m( F, S# i
to update-class-histogram% M5 {% j2 r8 ?: T( A! r
set-current-plot "Class Histogram"
, R. E2 R4 }" e" K' x plot-pen-reset* I- @; k# m8 Z
set-plot-pen-color red
, B$ a5 e4 ]5 L6 G o" A* B plot count turtles with [color = red]7 @5 V$ x# |8 b4 W% v( l
set-plot-pen-color yellow Y$ {% Z. P# d1 Q& l1 N$ K$ X
plot count turtles with [color = yellow]
7 \% y; B* G' v7 d9 _ set-plot-pen-color green @) p5 X2 p/ S3 L" W! w
plot count turtles with [color = green]& v$ Q% ~- I5 G- }) Z, q( s {- w
end
4 r( ^( \3 a! Jto update-lorenz-and-gini-plots- u- e) q' G- L1 r$ f% t4 S
set-current-plot "Lorenz Curve"4 O, H4 _6 S9 u: X7 R: T% Y& F
clear-plot8 l1 l# m n- P' x3 P" o8 Y2 z
3 ~# f) ?0 j( Q
set-current-plot-pen "equal"# W4 x0 c; [7 ]4 M& b0 L: m
plot 0
- R8 W/ J2 y# D3 o plot 100
# T. f" x8 ?1 j% S3 t, C; ]8 C9 T4 C# Y# n/ k+ k6 T% ^
set-current-plot-pen "lorenz"
' }% s o' W% @8 k4 E# o& k set-plot-pen-interval 100 / num-people
; y- L% ?' R' U1 l2 B. o4 y plot 01 k- _! y. t2 S+ @( ?
5 i: `5 _7 o! j" T: y$ M2 P
let sorted-wealths sort [wealth] of turtles# Z3 g2 ^, O) N* z/ }0 d# Z6 O
let total-wealth sum sorted-wealths
/ Q: n; g4 h; o8 }; p& V) W let wealth-sum-so-far 0' R: r& v/ y2 E6 `2 C& f& z
let index 01 l! R) y) E" X5 k$ N& |8 r& \
let gini-index-reserve 0
" v; x; k' _3 U; S: i, M6 G$ q1 r- p7 `) M
repeat num-people [# ], `( \5 ]0 I5 h
set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)
+ o4 r6 O3 x& y2 L: |" h plot (wealth-sum-so-far / total-wealth) * 100( Y, G5 d8 o+ y1 f# d
set index (index + 1)
; L% e) y. k) o: S4 E/ \* _ set gini-index-reserve8 X6 i$ K' s% f, V" X
gini-index-reserve +5 w; }3 U+ S; _% c7 d/ `- B
(index / num-people) -' D, |0 ^+ O- I* X7 }
(wealth-sum-so-far / total-wealth)7 e. L7 a; k* ]# Y0 Y- e3 o8 U
]
' P$ e, c. r7 b1 ]8 }7 K+ [! @
6 D3 R* c2 y( S% t+ m2 c9 C+ v set-current-plot "Gini-Index v. Time"$ i/ F L( M* Y) \/ [$ s) S
plot (gini-index-reserve / num-people) / area-of-equality-triangle
; b6 ?3 |" p+ {. m' T7 k3 cend/ g; |9 O% s2 p) z/ k& D
to-report area-of-equality-triangle' D: J, ]9 O1 U4 n& H `% @* Z! p' G
report (num-people * (num-people - 1) / 2) / (num-people ^ 2)
9 @; [ S( H8 A% y; Aend |