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
4 a# E& u1 q) z$ {, m' U* K0 Fglobals5 Y) c3 P& g0 A# `
[
, _9 i$ Q k8 Y; }" h+ n, w9 G max-grain / S) ^6 b X; q R3 U
2 p5 q1 s# w! ^9 N( [9 }6 f
]
+ B$ ~# m: ]$ m9 u) ?( W; h+ ~2 L# t: C
patches-own, j+ @6 \$ n9 ? K( N+ F
[
6 y; B+ t6 i1 C' j/ E grain-here
}' [. I i9 K max-grain-here
5 E# ]" @; ]4 ~]
7 f- U }3 g5 b6 R2 G. E% Z. U* I: M
turtles-own
, N9 e O) i: L( {[
# _) h3 R/ i! R' E7 Z age * m! I1 s/ t' a+ a1 f
wealth $ n5 U8 H: Z# v6 O. [2 _+ M* s# w( _6 e
life-expectancy
) d3 W5 r9 P1 d% x8 z4 C metabolism 8 D& x9 y# j3 X+ B7 J' P
vision' J0 Y* \6 Y5 B+ S
inherited
h% g0 i3 N9 I/ \0 x: N]
7 c8 M' M+ O2 a# V. _" S n, t4 j7 H
9 d: D/ _. }7 J5 B; |* i h, y1 g( ~to setup
4 Z* n! @1 e2 T; Z3 j/ U& a ca& ^+ E2 j! Y" {7 p& N N
set max-grain 50! V3 r" B: ~5 G8 p7 q! w9 J
setup-patches
2 J% @+ Z4 @7 l) E. ~+ {- s% `) V0 P setup-turtles
- q% t+ n. _% N setup-plots
0 z* g6 @2 u5 N update-plots
& x) R9 f2 t( w# \+ Q4 F0 } ]% C5 ]end
' L7 d" i3 v+ I. Y* ^+ tto setup-patches9 p7 Z$ y+ _ W
ask patches
( ~2 d, k/ I* C+ B [ set max-grain-here 0
- G, o, k( i1 c0 v( D if (random-float 100.0) <= percent-best-land' x& s# x% Z( z c7 i# J9 d
[ set max-grain-here max-grain& Y; x6 O. O/ f) q5 g! k
set grain-here max-grain-here ] ]* r! N! c- q t$ C. v/ J. q5 B
repeat 56 j7 O `1 M' @* r6 H. g: ^+ c s
[ ask patches with [max-grain-here != 0]
! z3 q! [4 T- |9 L$ H [ set grain-here max-grain-here ] d% y$ n5 G+ W4 _( U$ T- [
diffuse grain-here 0.5 ]
: V2 Z1 i; V" c- I9 V) @ repeat 10 P2 K+ i0 M7 `9 j7 g
[ diffuse grain-here 0.5] % H/ Y0 {8 ?1 I9 t3 Q+ A2 A$ j* s
ask patches/ T/ d: E7 n3 o# u; }. M
[ set grain-here floor grain-here 5 U( p$ j% h: a ?
set max-grain-here grain-here
# V7 s( ]4 S, k/ e3 o, x recolor-patch ], |& i+ p- l$ k, L/ C
end
# I$ H9 w0 @- d! ^8 z7 \to recolor-patch # U$ v3 n A! b7 G
set pcolor scale-color sky grain-here 0 max-grain
" M% Z! }- B F7 P+ T& |5 @5 Nend
: u$ S# f- a N7 [9 |% T3 {to setup-turtles
2 Y3 a# {4 H% Q. C6 \ set-default-shape turtles "person"4 M, U" }( T/ p" e. t" p
crt num-people; r7 h) N- q8 l5 x
[ move-to one-of patches 7 E5 c; Q# ^8 `' F0 k
set size 1.5
2 H& Y& o% ~5 w4 v set-initial-turtle-vars-age
3 P6 ~7 K) m, E/ Q, B5 i# k- m5 r2 z set-initial-turtle-vars-wealth* x N3 u. i+ p
set age random life-expectancy ]
- c# u& q7 z# v' E# b% | recolor-turtles
+ v2 l$ w( p& T' P2 Yend
z' S- s4 G. p6 Y, ]8 q/ ~6 o! \9 Y9 V; U% B8 d z' U1 s
to set-initial-turtle-vars-age5 u( V3 F3 x7 ~5 T: J2 \' f, K# w9 c
let max-wealth max [wealth] of turtles$ G3 G/ l: v0 u
% ]9 Q m/ B% k T8 l ifelse (wealth <= max-wealth / 3)+ A1 O8 m4 M& J, k/ N+ b( t$ V h
[ set color red S$ ^% g+ V: N6 w0 [
set age 0# H, `( z6 y* w, {7 O* L
face one-of neighbors4 - f1 W% u t) U+ s- M# b! R
set life-expectancy life-expectancy-min +
1 V( U% Y" o" ~* ^ random life-expectancy-max 2 r8 K7 p0 e' x
set metabolism random 1 + metabolism-low
- }; x( m: u" `3 K) [ set wealth metabolism + random 30
5 w2 z! S' U+ z, G1 ~) r( M# r! r set vision 1 + random max-vision1 S g+ H% W- |& y
set wealth wealth + Wealth-inherited-low ]# J3 @- ~( }, Y+ P/ W
[ ifelse (wealth <= (max-wealth * 2 / 3))
: J) ^- X3 A6 N6 ^ [ set color yellow * m& g! a$ g1 v2 t3 ]6 w0 V- r
set age 02 ~+ y# B6 h2 C9 H1 h
face one-of neighbors4 - b$ k+ Z1 w5 }+ ^: W7 c. q/ T
set life-expectancy life-expectancy-min +
: R- l* H+ C. q, ?9 ~! ~1 ^# ? random life-expectancy-max + 14 b6 u& R2 ~* d% O0 U
set metabolism 1 + random metabolism-mid
4 o% y4 |! h' D$ ^$ F set wealth metabolism + random 30" k- T3 ^9 s h3 U+ g. T# [
set vision 3 + random max-vision4 w7 y, _& c+ r$ r* F
set wealth wealth + Wealth-inherited-mid]( q. i0 w1 Y$ U% d! j4 C( l% [; A
[ set color green
' m# L$ F& c5 C5 N6 E+ z set age 0* {' ]- m9 y& g6 S4 j+ B0 l- }) J) j
face one-of neighbors4
3 Q ?5 J7 @, ~* F2 F- F set life-expectancy life-expectancy-min +& \7 a9 ?2 b z" `7 P% H2 O
random life-expectancy-max + 2
& V. l0 X* r. ~7 Y) k9 k set metabolism 2 + random metabolism-up, ^ [" C5 _+ E7 J5 ?; `5 e# j5 T
set wealth metabolism + random 30
% C+ [8 A; G L set vision 3 + random max-vision
8 [5 @* c$ ?! d: Z( y set wealth wealth + Wealth-inherited-up ] ] - G" @" u: a6 O
# O7 t7 V, X6 @/ s5 _. Z! x7 a/ bend! B: N9 E( B+ T8 t- F8 M
to set-initial-turtle-vars-wealth
! v- F3 Q" V+ A" Z3 Z( W let max-wealth max [wealth] of turtles9 h& h* U1 z8 \$ R9 U( W/ E
set age 0$ }/ K' {; `' r0 y
face one-of neighbors4
' X1 O9 X l$ L2 P1 v. k* Q. d# N3 D set life-expectancy life-expectancy-min +* V0 ~2 Y3 o) n7 K" u6 J2 w
random life-expectancy-max + {2 S+ U' C+ W8 p0 T% }3 a
set metabolism 1 + random metabolism-up6 P r/ i# l! l: B6 V7 O# R# q
set wealth metabolism + random 30
$ D, z0 L0 g1 h) o( _ set vision 1 + random max-vision
: J$ ^! F4 n- `+ K; Wend2 u) c# E/ [+ I. L( W
to redistribution
- y3 [" D O' ]8 C3 l! X+ f5 ?- Alet max-wealth max [wealth] of turtles
6 k/ o2 K+ i3 l4 o/ q$ T$ t- g" nlet min-wealth min [wealth] of turtles5 H% T0 H! X' W' g2 k+ ]
if (wealth <= max-wealth / 3)
/ U0 z7 O5 B" |' y [set wealth wealth + Low-income-protection ]. L4 M& `4 g/ o$ L! g0 k8 X
end
! g; ^$ C# _) _ & N. y1 F* |/ k% }2 |- ~5 x% s
to recolor-turtles
( ]0 r2 W+ f* B! i& F$ }6 D2 ?$ ]( S let max-wealth max [wealth] of turtles& t' F/ p# v/ d7 L; v
ask turtles
3 J9 D0 ~$ @7 w! [ [ ifelse (wealth <= max-wealth / 3)( C. ?+ X1 n o
[ set color red ]. C1 O: R6 g8 t
[ ifelse (wealth <= (max-wealth * 2 / 3))3 s3 {+ F, {* J7 x$ S
[ set color yellow ]% A8 P' @7 b; H) E) B
[ set color green ] ] ]- I' M0 d1 Z, D0 V) X* f. n* J# d. ?* ?* P
ask turtles [ifelse show-wealth?
2 L& c$ c# n$ Q+ q0 T0 ^9 s [ set label wealth ]5 D# O# f1 V0 L5 o: X, r2 r- D
[ set label "" ]]* \6 v- t( \. Q- `; v4 V! s0 }
end* e+ W! S4 h# W9 B8 C6 u3 H
/ R$ l5 J# R, U5 Q
to go
9 g$ _. d- s- f8 I4 W6 m' ?+ _, J ask turtles$ N3 Y M {+ M6 ^
[ turn-towards-grain ]
+ Z% |1 t# M5 O' H! N' u Z harvest2 } @; [/ q' @
ask turtles+ {) q2 d; C+ _- x7 B
[ move-eat-age-die ]: ^& Q6 e% _$ k* I% l
recolor-turtles
- _1 a& r# }/ `) Y, D! e if ticks mod grain-growth-interval = 0& Z, Z8 H( }# `. `, H4 _/ T) H7 S
[ ask patches [ grow-grain ] ]: c% V, R" B" R ?5 ^% z7 Q
: J* ~+ h) B/ D g- L
if ticks mod 11 = 0
, |5 d8 l0 q( t7 z [ask turtles
z) o& J0 R E: p [ redistribution ]]
5 m ?3 e" L/ M if ticks mod 5 = 0+ y1 q! G, F& Q o; w
[ask turtles y' Q9 j, ?+ i m7 w7 `2 x5 j2 k
[ visions ]]& u* ^9 T) l2 W& O; X& j; [4 r
tick
8 d3 H5 i E3 g$ P* _1 B update-plots
" g; d: i6 b2 v+ tend5 w3 U& Y( T4 ^1 ?$ @: `# V
to visions: n+ \3 R9 e0 q( u5 M1 O! K
set vision vision + 1
# O; S4 L m/ d0 R* u5 aend/ X9 D$ c1 _& O" n
7 C2 u3 j9 V8 d( d+ D$ O% t- o$ M# {: z: A1 P
7 k3 q, z2 N$ b3 S& a
to turn-towards-grain - Z ?( Q8 B/ G% z3 q9 ]' o
set heading 0% M- S) l7 X% ~* t: n
let best-direction 08 ~7 a0 G- e4 u% m
let best-amount grain-ahead
2 u7 c& m; O1 E3 A& \ set heading 905 `. x# G0 q2 ]- N2 M' h
if (grain-ahead > best-amount)
# w8 C% n9 _. p/ K [ set best-direction 90 M! }9 r6 m* r4 C
set best-amount grain-ahead ]
& J) i- b% D7 t9 x set heading 180$ q( I% i$ }1 ? u
if (grain-ahead > best-amount)' H6 ^! z" v7 b0 _/ f* ^5 q/ g8 s
[ set best-direction 180* F- X- z8 X, ^- B, _8 X
set best-amount grain-ahead ]; ~5 }6 ~' Y$ e3 r5 m# Q, p
set heading 2706 k9 k- w0 F: y, `# f( N8 @
if (grain-ahead > best-amount)
, g, }$ W* ~* y) M4 }3 B/ l [ set best-direction 270 \* p( J* H7 R, L
set best-amount grain-ahead ]5 n( ]& n# Z A1 e% a
set heading best-direction
* } S! L8 `1 o, W i, oend
5 i$ _. o/ N$ \9 i, D: _
8 I- i+ F z6 S0 ^8 X
" A1 J' G* |7 ~/ Zto-report grain-ahead
9 A5 j' x0 Q9 W% E: O/ G let total 0; L2 l8 H9 \7 G a
let how-far 1* T' g1 X5 H$ R! q
repeat vision
: {( ]# U% k' C- z [ set total total + [grain-here] of patch-ahead how-far' J! i. S8 M; N+ J$ u5 Q
set how-far how-far + 1 ]; O1 \- X; }3 M8 Y
report total
7 `% J+ T( z3 y$ q5 K4 dend
- E' S+ S4 c. X" W+ G* }! f) y9 p6 R2 B; d A
to grow-grain 3 l6 O& S! C& ]2 e6 B0 J
if (grain-here < max-grain-here)% ?, z2 z( o, H" i; [ s
[ set grain-here grain-here + num-grain-grown
$ U5 \: o& X# O+ @1 k if (grain-here > max-grain-here)
; y8 {8 V+ _, l4 ] [ set grain-here max-grain-here ]& z# h8 s4 i3 K- a. V) V
recolor-patch ]; S! I9 m: d/ y0 b6 }
end
5 B/ U; G' C$ u6 l( r% Fto harvest% G8 F2 \4 r( c1 q# `2 K: i4 H
ask turtles
9 p% m7 W5 ` G( [9 ^) m! _& a [ set wealth floor (wealth + (grain-here / (count turtles-here))) ]
+ I' r' j h/ Q7 @+ L ask turtles
4 W$ x8 }! Q0 C [ set grain-here 0
c# x+ e+ x# L8 s) h7 e- ^. y- M! _ recolor-patch ]/ I/ v3 ^' p9 Q
5 o# e; }0 |) \ q6 C: U0 b8 oend
* S0 S& Q' y; ^7 X
$ Y) ~- |$ o. m _- ^# `to move-eat-age-die , y! @4 p# r k
fd 1 n0 v& `3 s+ H) O* {
set wealth (wealth - metabolism)
) o( w/ }- P1 {5 t4 J! _ set age (age + 1)1 x% } ?+ e, N6 e: g0 s, G- X* w
if (age >= life-expectancy)
( T7 G6 }. E! {! |! `: T# H [ set-initial-turtle-vars-age ]
: N, C9 i' H- s% c# H if (wealth < 0)2 u" L9 d) }+ l- _5 w
[ set-initial-turtle-vars-wealth ]
4 h+ I7 ~ d; x) [9 E5 V3 d
; A4 G6 N6 w( aend
1 H- f! ?5 n0 V0 u6 J/ V, _1 o; ?7 H% j7 C2 F) p
# O7 H# e6 h# t# k- |1 x1 [: s
to setup-plots$ I5 L z2 m% u! p7 D" S
set-current-plot "Class Plot"
* Z$ c" \; S" y/ g7 b" O5 P2 B set-plot-y-range 0 num-people
) L) [$ o. ~) d- e- H% _7 L set-current-plot "Class Histogram"
$ u; S! I& \ i4 V% m/ B set-plot-y-range 0 num-people
* z7 @! C+ X( v% ]4 a2 z" B/ qend
7 e% k, T7 S N
9 N- l [9 R" a% j: Y1 [to update-plots
/ o2 L9 _5 x, c1 T update-class-plot
. k( s+ G& M5 k% z' Z update-class-histogram
# E8 |- s* k$ K% C1 e. B: d update-lorenz-and-gini-plots" B8 X! a( a" c! j+ ^) R. b( J
end( O$ Z y! H4 v
6 x. Y. t0 v0 I+ K6 ~: e& A' b; x1 mto update-class-plot& D, F( P% l, M! W" c& G" i R
set-current-plot "Class Plot"
3 R# N# S, }* _5 e set-current-plot-pen "low"
3 t: @+ [) f4 O& U/ x plot count turtles with [color = red]# }( Q+ b1 j8 \) }8 v0 Z+ {
set-current-plot-pen "mid"- T$ ?% A7 S1 r( S9 C- ~. m1 n
plot count turtles with [color = yellow]
3 {3 n+ y. r, \ set-current-plot-pen "up"
9 t1 Y H+ E. }# r! d0 `/ Q plot count turtles with [color = green]) {- ^7 F, C8 W
end
! L2 g7 M, F6 a3 M7 r# q0 `- f R- m" B& [4 n
to update-class-histogram& q2 d* {% m+ [: R: i+ }/ m, p
set-current-plot "Class Histogram"* B( Q6 i6 p8 C+ r
plot-pen-reset
8 P4 x* b, e: G6 P% Q0 ~# b set-plot-pen-color red
' J- y. X$ w: T8 T plot count turtles with [color = red]- f. p0 }1 J5 _' z1 v4 H2 k/ [
set-plot-pen-color yellow
/ ]% }" K" y5 U. i9 \ plot count turtles with [color = yellow]- n! Y8 e7 ?3 Q9 B# ?9 w
set-plot-pen-color green
) M9 C* J/ S7 a/ U plot count turtles with [color = green]& R. m0 n, W3 ?, R
end
2 \# `5 J9 v5 k. l- ^9 H5 qto update-lorenz-and-gini-plots
8 ?" c/ n, a7 V set-current-plot "Lorenz Curve"
! c. o3 M3 `/ P9 n K0 U7 L clear-plot4 X9 Y. a$ v0 ? K$ P$ w
* |* k# E3 t- P% s9 a3 f set-current-plot-pen "equal"
: J. U7 v5 z. r) q plot 0
. \1 ~; V! I4 W2 w plot 100
$ T! |. m( S! B$ t2 z, U! T$ d8 f$ r0 D" K _& [3 }. k
set-current-plot-pen "lorenz"
! a; {/ l! z$ F& r; T5 Y& Q set-plot-pen-interval 100 / num-people9 s9 @! r; T- Y8 \) v, s
plot 01 R7 x+ d+ F% e2 G- o- z+ n
4 C5 n$ p6 e8 f* _9 y5 F
let sorted-wealths sort [wealth] of turtles8 q1 v# h. `4 L& ^
let total-wealth sum sorted-wealths5 {9 n% F5 z, A
let wealth-sum-so-far 0$ B! ^$ Y. f4 x% H2 \
let index 0
& S, ]/ Q- N m) A. R( P( ? let gini-index-reserve 0
( b" o' T# B" a/ A
3 o, [ c; q# K4 l repeat num-people [
4 X* }0 J9 o$ L# V. a set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)
5 }& H$ q% K, w% j! E& H4 m# W plot (wealth-sum-so-far / total-wealth) * 100
9 F: f% R( V5 D& v set index (index + 1)
# H+ J! h# k* n/ D* `" H set gini-index-reserve6 p: O' |; q: Y0 e
gini-index-reserve +
# y( {3 x' q4 G% [8 c (index / num-people) -. `* O. C9 ]+ }5 K3 F
(wealth-sum-so-far / total-wealth) |( s+ K/ [- H; c& M% W! C
]
" v, _# {% ~8 C( A, m* b8 W! w( p- Q) Q M
set-current-plot "Gini-Index v. Time"
, h/ z3 [/ F8 K# f5 [* g8 { plot (gini-index-reserve / num-people) / area-of-equality-triangle. S5 I- K& {' _; P+ R
end
' e, i1 U# C( `- j$ Kto-report area-of-equality-triangle
2 b5 o+ ~7 t6 B( p7 O report (num-people * (num-people - 1) / 2) / (num-people ^ 2)
" U& S2 W" S1 a$ d# C; `end |