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
: W! f! F8 B* X. Jglobals9 T6 G: D5 `# z& t, f; f
[
, n. v U/ G7 z3 E) K max-grain
: d2 w) B: L U+ i
R! Q$ d* m5 x, M]
3 R$ }- f/ e0 D; K, d& f- E+ l+ d' s1 Q
patches-own. |" B1 w& R2 M4 J( O
[, y3 D7 d7 f$ I3 G/ |( t! q
grain-here
- B% ]" W$ r, ]5 i3 h, n max-grain-here
/ {' q) o- b& [5 @; b* c] Y4 W1 n) R) M
7 Z, X" f. D8 B& C" E+ m
turtles-own# `6 }' C0 r0 f3 i/ e- ?' g* o
[
1 M) M# ?, x! W$ Z }9 W age
. r9 ]: q' Y2 @: g2 X4 T wealth % \- f! Z+ l+ O, x
life-expectancy + @- E/ T4 ^4 p6 A' F! y
metabolism 1 I& o8 x4 [. B) C) {
vision6 A/ \" u. B. Q* j
inherited
" p+ q3 u; ?- {' M]
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; a" S5 a/ u& L5 l. V
8 ]# i# E \2 ^+ G, B/ t9 Sto setup
( z' P O+ J2 X$ ]' `0 p" Y% o ca
: k3 z" Y0 c" t, a4 N set max-grain 508 X5 @5 Q7 |, X. x {6 o
setup-patches6 x5 Z# s! K* x
setup-turtles
. P3 v. P: t+ o setup-plots
1 Q! d1 ^6 O8 B update-plots$ i1 U: Y$ T' G0 L' O9 N
end
S k8 w8 \3 V/ Sto setup-patches* R7 w1 O/ T' F$ p
ask patches
' q- i8 H8 T ^% P2 x6 G4 ?/ ~3 m [ set max-grain-here 0 q4 `8 J- m! l" V! p
if (random-float 100.0) <= percent-best-land
$ [" M1 d- [; V; ^8 G$ e; ^2 j [ set max-grain-here max-grain5 r( L( B; K: A( D! Q) V
set grain-here max-grain-here ] ] D6 I) _9 ]) r% J1 y; C& j
repeat 5
, B& T- M$ k4 x3 X. i* q% i e+ n [ ask patches with [max-grain-here != 0]
+ p: n8 l6 a0 Q$ ~ [ set grain-here max-grain-here ]4 h' S) i7 L2 H' ^. d1 M
diffuse grain-here 0.5 ]( u% C6 z: g' r$ c
repeat 10
" u9 u2 x6 E8 d+ a [ diffuse grain-here 0.5] - c* U9 ^/ `5 Y0 f: U5 T& r
ask patches
9 [* L8 c7 A; |/ B6 ] [ set grain-here floor grain-here 0 H& H% d' @; f, U
set max-grain-here grain-here
! s( y( {1 b& C- N L5 }. h recolor-patch ]
$ S5 n1 x) C0 l, [* O- Bend9 w% m5 ?) I6 b. |4 K4 e* C$ `1 w
to recolor-patch
7 ^, }; W- p- j. u% |& C set pcolor scale-color sky grain-here 0 max-grain
# K0 z1 H' U; A0 o) C# jend, c, t& k1 n# \) X' i- l- q
to setup-turtles
, [) r! n) g9 E7 Z* i; l+ R8 `! Y set-default-shape turtles "person"
% [' m; H9 a9 Q0 [' j5 B+ @ D crt num-people7 I3 d2 o: m- b1 r) ^
[ move-to one-of patches ( o( w8 q; a' C% j. x
set size 1.5 # t8 s5 N( u2 p
set-initial-turtle-vars-age
& D5 e9 t( l8 h7 r set-initial-turtle-vars-wealth. F, [( [! [& i5 c( @
set age random life-expectancy ], e7 v2 X% U3 @
recolor-turtles
7 C: V/ x; B Y1 I6 g- {6 k& ~8 jend* m9 p- Y8 `0 c- M1 t
4 ~" x* n. p0 _, C8 kto set-initial-turtle-vars-age
; U6 R& Q- x# l; B let max-wealth max [wealth] of turtles/ Y% d% h6 [" U9 Y1 K) `
8 c: S3 D2 D0 j# c
ifelse (wealth <= max-wealth / 3). w" l, D1 A- K" M1 O+ m! D
[ set color red * u9 ^, `. q% E, Y
set age 0
2 z5 x6 [2 M4 q- Y face one-of neighbors4 . i7 {4 x& G' |3 Q* {2 f$ s) O
set life-expectancy life-expectancy-min +, g) p& v! h* U2 M
random life-expectancy-max
4 S% }' n. o1 F7 n, l3 F1 C0 E set metabolism random 1 + metabolism-low
- X( U* ^4 S4 } set wealth metabolism + random 303 Y; N }. I$ C! S: @
set vision 1 + random max-vision% l4 I6 U* V$ m+ O) q
set wealth wealth + Wealth-inherited-low ]: j! l2 f1 O4 j4 Q
[ ifelse (wealth <= (max-wealth * 2 / 3))
, u6 T& k; R) S B3 Q [ set color yellow
: G( E0 n) n0 C% v. E set age 0. E! q' t$ |/ ^# o; D
face one-of neighbors4 : p2 P4 e: F6 A0 e/ V
set life-expectancy life-expectancy-min +
) }+ j4 L% h7 b) x: U7 w- D; _ random life-expectancy-max + 10 V% {& x" @) h S* N3 _
set metabolism 1 + random metabolism-mid* \5 \" |6 R8 ?! P( l; R7 m! u5 I
set wealth metabolism + random 30+ i% p# ]7 m$ e8 F' k$ m
set vision 3 + random max-vision
4 n$ Y$ z/ H b set wealth wealth + Wealth-inherited-mid]; s# s* l6 V9 t4 e* v3 Y7 U% t z4 K
[ set color green
% | |- B x5 Q, K8 y2 @5 m+ v set age 0
2 W2 q2 K7 {; |- _ face one-of neighbors4 + j; y w- R4 Y* K
set life-expectancy life-expectancy-min +
7 b+ t" E$ }5 l% V8 V" N5 ~+ { h random life-expectancy-max + 2) f0 W0 m: z ?5 [3 S- T
set metabolism 2 + random metabolism-up, k! q) d6 A& v: k, E% O
set wealth metabolism + random 30
- R. X" F+ D8 R# ]; r set vision 3 + random max-vision4 o- w- L: f a( Q" t
set wealth wealth + Wealth-inherited-up ] ] ' Z" z- `# D7 w4 X) ?
* P! d; P5 {; tend, R) v: C- T- ~6 H; E2 z
to set-initial-turtle-vars-wealth- `( ~0 F5 p, t7 @- P& O" |
let max-wealth max [wealth] of turtles, o3 G6 e! p1 X( M' n: \
set age 0' m$ }& V2 P# A- ]5 a7 I( ^
face one-of neighbors4 & N) Q2 @: j' o8 P* c, Y
set life-expectancy life-expectancy-min +
; q1 h/ n1 Q' Y/ Q" O6 G8 f6 a random life-expectancy-max
* G" m3 k- c8 j v: N1 b7 ] set metabolism 1 + random metabolism-up
, K: ]/ [% [2 h$ A: M9 c) N/ N- { Y% q set wealth metabolism + random 30# f9 n5 C% a& Z$ p0 K/ N7 g5 I
set vision 1 + random max-vision
) a# X! z% P$ w6 k3 R* Gend2 q9 p: ]( l& M* h( ]
to redistribution
6 w- s; ?, v: g; M8 zlet max-wealth max [wealth] of turtles3 f( r8 b7 w9 U! h! F
let min-wealth min [wealth] of turtles& P# Z( P( }$ B7 k5 O7 s( ]' L4 D
if (wealth <= max-wealth / 3)
! t. }! X- j, k$ h( S% M ^7 w [set wealth wealth + Low-income-protection ]1 u9 f3 k# S# r$ h6 `' ~. |
end
& c3 U7 \+ k, o5 b8 j' f# M( t
2 A8 j/ o- P/ c4 dto recolor-turtles
6 H2 M& x }" b let max-wealth max [wealth] of turtles
+ r9 u+ u8 H9 s ask turtles
$ T0 O) H2 H+ G. A( s [ ifelse (wealth <= max-wealth / 3). m* W5 \# T. W* b( s* \8 h0 K# J
[ set color red ]5 r2 b; A2 ~' v7 T
[ ifelse (wealth <= (max-wealth * 2 / 3))* D: W5 N; D) e% r* y
[ set color yellow ]3 X- L6 a. t) j! f6 j
[ set color green ] ] ]! c2 `* P- z8 W9 b$ z6 Y" t% T
ask turtles [ifelse show-wealth?
3 X9 B- _) i( c5 ]9 a6 h1 g [ set label wealth ]3 ]) h4 M3 d, {# A7 i" q
[ set label "" ]]! y' a3 ~8 Z& a% s4 g: ]
end/ X+ b( n. g4 i- v2 J# Q% h
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to go
' {5 U6 ^: U5 e ask turtles7 }; L% N( s2 t8 o' t
[ turn-towards-grain ] 4 H/ l* e7 l8 M, I5 [
harvest ]$ ^ y, }' y, q6 c
ask turtles
! \/ u$ a% J4 q: J [ move-eat-age-die ], P0 F$ u3 y) ~
recolor-turtles7 @7 j! L$ D+ D
if ticks mod grain-growth-interval = 0+ F5 l) A3 Z$ y- w* i" k' y
[ ask patches [ grow-grain ] ]
; J$ { V9 F# X8 ] " S! k. U6 u- q5 u. X
if ticks mod 11 = 04 Z5 g6 Q# V$ d- T
[ask turtles
3 M! y* W+ [+ H' h' S/ M4 q$ } [ redistribution ]] q1 n2 p0 z6 g
if ticks mod 5 = 0
& N' f% v( A# ?& B5 o [ask turtles! z" p: ?% X# h1 B9 s: n: G
[ visions ]]
0 K5 l' ?, k, @- [, c/ H tick
' h' P! G+ G; q9 @+ [8 r+ c3 ~ update-plots
, H2 G9 f3 B( V1 q8 V( ]end
+ P; u+ i' s4 z' t. a2 q$ yto visions0 v0 `. L3 D/ a6 e% g: ~- R5 z
set vision vision + 1
# Q, y" g( A) \: ~6 B$ nend h3 w# ?# S% Q) t
) \5 _$ W& n( v+ Z/ a( u
0 v5 [* Y- @: M+ R; n' E7 t v" Q4 b. l& P) a
to turn-towards-grain
# h) ?# u* x% V6 O% I set heading 0& Q4 P5 e/ b3 p$ |& w* ^
let best-direction 0
+ G- V5 z! C" S$ u let best-amount grain-ahead
) Q9 ^+ u2 T3 J set heading 908 L$ D6 ]1 t9 P
if (grain-ahead > best-amount)
' |/ u5 ?7 e0 A* W3 s9 n; d [ set best-direction 90
3 j1 Y: }2 ?# x7 d, ^ set best-amount grain-ahead ]9 q1 U I S; U5 o9 E, {% F
set heading 1803 L# h! g$ _% S9 @& W$ s
if (grain-ahead > best-amount)5 u+ ?) Y" I8 R- }, `
[ set best-direction 1806 M' v/ b4 c- K3 p. Q9 t+ M) Y9 m7 R
set best-amount grain-ahead ]9 `8 w, p; E' w1 F. D8 J5 h; V
set heading 270
* r) o; {6 O/ l1 y if (grain-ahead > best-amount)
% G, d/ l" }. w, [! j0 u [ set best-direction 270
! F' J' X* S( C0 `' e9 O set best-amount grain-ahead ]
- T5 \% h3 F: O1 @ set heading best-direction
/ a5 t, K I: Z& m& ^end
( V* N# [. u: r6 ~1 Y3 H( v' A7 _2 k! y1 ^8 H
; r7 _9 o2 m' L7 C$ g' H* \to-report grain-ahead 0 h3 C* B, \" _0 `7 u
let total 01 f: u3 x4 d0 Y- ~' k
let how-far 1
% \$ ?" Z! }$ S0 S1 `; ~/ h repeat vision: y, \# G* m/ J3 l8 T
[ set total total + [grain-here] of patch-ahead how-far
# F3 Q1 D6 r+ p! y set how-far how-far + 1 ]
D- t2 k; Z! J1 L report total. [- Y* W5 p+ f' f1 E( Y8 _* P) Z
end
+ B3 Q5 \# R/ T. P3 p. o
% Q$ G9 b+ h) b+ o! m7 \& C$ rto grow-grain
6 k A1 m. P# i$ O# s5 X5 o if (grain-here < max-grain-here)0 a4 W2 ~/ |1 j& i D j M3 P: M
[ set grain-here grain-here + num-grain-grown
5 i' u- Z3 s6 {- c if (grain-here > max-grain-here)
, p9 m$ U" m3 X8 _ [ set grain-here max-grain-here ]. ~7 x% q. O% v
recolor-patch ]
' |$ A; w, l U& jend
2 v1 t# z* _- b* v$ Bto harvest
: S1 v( m6 \9 ?, m1 K ask turtles
$ B& J! l# Z; f: i! b [ set wealth floor (wealth + (grain-here / (count turtles-here))) ]
/ T) G0 M7 W- f0 Q; z& Q ask turtles3 r; Y# X. N4 Q; U
[ set grain-here 0* [5 ~ r, C/ ?2 J! P% R+ Z
recolor-patch ]. t& `' b; e4 ?( U
, }4 \' q$ M% P! _' m hend
1 n2 z4 E- R/ }8 B9 T, F
/ k* d) q+ K& T L& \to move-eat-age-die 0 N! ^! e* u6 ~7 {! _& O; ^- }
fd 11 g$ i. t+ ^' ]/ J# K0 V K4 Q
set wealth (wealth - metabolism)' B3 u6 u( V$ L4 \) {6 V
set age (age + 1)$ V! l9 a9 g( y0 B; S l6 K( g
if (age >= life-expectancy)
; L# I5 a0 j) @3 ~7 Q [ set-initial-turtle-vars-age ]
' Z9 w. P/ w! D9 m$ ^ if (wealth < 0)2 S( i' Q1 J/ X
[ set-initial-turtle-vars-wealth ]
) H3 l9 i* f- P9 r( w' v- L, r
- m- l! Q+ Z! ~* x' @end
! M& S: Y+ y" O" n: N, ^) C/ z* @
+ Z t& }* v- ?. n$ m8 d M+ G
+ x% b- g6 V9 y5 ito setup-plots1 A8 a+ K: K. y
set-current-plot "Class Plot"
( q# N& [/ \- j( |% I1 _ set-plot-y-range 0 num-people
# {" m. V3 q9 F3 E H set-current-plot "Class Histogram"
7 e) m! | K- i/ U5 T) s set-plot-y-range 0 num-people, p6 |4 l) {' _# l# H9 k) B8 _% z( L
end
' Q7 S9 q% V; F$ E9 J6 Q0 N5 {% P( e; S1 k8 Y: C! x* O
to update-plots, v; L' R, @" |$ d4 N. {
update-class-plot
+ _1 {9 Y' k) t' y5 U/ @ update-class-histogram
' k9 D5 u% E6 q$ B: u update-lorenz-and-gini-plots' [+ h' _4 ?( ?; i( b
end
7 `' y2 g/ V: g0 V% g: L
6 p$ R- ]% C5 ~/ x8 Hto update-class-plot& q4 l! H5 r$ }
set-current-plot "Class Plot"- @8 x/ c; O" f' g7 {+ } u( {1 ^" [5 p
set-current-plot-pen "low"
' R- s7 O M. [: ~ plot count turtles with [color = red]
& a7 S7 M/ _4 b6 x, Q7 ~) j6 j- P set-current-plot-pen "mid"! d6 ?7 U9 y9 V! F1 t+ @
plot count turtles with [color = yellow]; r$ Y+ ^, l: m
set-current-plot-pen "up"
2 M7 t, V$ h6 R( i plot count turtles with [color = green]# ]+ {7 k, o$ g; \" o" `# ?8 D' L
end
$ N* ^/ u4 G6 O5 c9 x8 N$ d3 N$ w1 `' b8 J7 v+ n1 `
to update-class-histogram
$ j7 T+ ?( J( N set-current-plot "Class Histogram": }5 |7 l5 L8 M. h0 G7 g' x6 X5 s
plot-pen-reset& r+ w9 F" W) G8 S- U* }' T* S
set-plot-pen-color red; A1 t0 V# g7 s; W& A' D: \+ K
plot count turtles with [color = red]
b1 K& M1 z+ K. ^/ j+ e; v. ~ set-plot-pen-color yellow1 ~& v; G# u# q3 `( g: X. C) Y
plot count turtles with [color = yellow]
7 A* r7 L' C8 j set-plot-pen-color green
. M' ]2 ?& @& @+ F plot count turtles with [color = green]2 w! b8 C9 q0 o! T) q
end2 k4 g. B$ Y7 [) s# N
to update-lorenz-and-gini-plots
! y) I: U" f O, j( O( [5 E- Y0 b set-current-plot "Lorenz Curve"% ]& [8 U7 {3 ?
clear-plot
+ R4 H8 e" _2 N! ]
; x/ R D7 H5 x) ?1 V: g set-current-plot-pen "equal"
3 A# }/ P0 @4 ]; @ |% P8 C plot 02 w; O9 }4 I) K4 v
plot 100
5 ~4 e3 Y8 J( a+ D) M" `& R
' ?+ r5 z3 j; N( f0 R set-current-plot-pen "lorenz"0 z s- Y4 \/ K" D0 ^
set-plot-pen-interval 100 / num-people9 [) [) F' }$ [3 }8 R/ w) t9 V: g
plot 0
# l8 I" E+ D. V0 X
; Z7 x0 X e- }9 T' e* l- ^' [+ i let sorted-wealths sort [wealth] of turtles
4 b A5 N, p; b) L+ z% [ let total-wealth sum sorted-wealths8 c# L3 \( C8 H$ W
let wealth-sum-so-far 0
+ j/ T C( C( q' Q+ h6 Q. I! J let index 0
* w2 z0 n, U5 v% g; J* L let gini-index-reserve 0' N6 o5 y5 ?! S4 I8 _- O
. d6 t9 t+ @ @; H/ J } repeat num-people [
% h8 N, c" P7 V set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)
* r3 h" i! L! @8 |) Y plot (wealth-sum-so-far / total-wealth) * 100( Q2 A+ M$ n) W3 }
set index (index + 1)( V9 `* @& m4 Q3 p1 F0 c$ ?+ ]
set gini-index-reserve7 r+ A" [. j9 E0 Z& a G4 A
gini-index-reserve +
3 E, P: `; I: x# } (index / num-people) -
2 w! A4 v3 F: L9 J# I9 g9 }- q (wealth-sum-so-far / total-wealth)$ v. e1 ~+ M# r% P' S4 e: I
]7 f+ E3 M5 a7 i7 w6 x! R8 i2 a
0 o5 w9 B/ L/ n( v8 Z6 H+ L$ ^. d set-current-plot "Gini-Index v. Time"$ t5 Z6 r3 X: m! I5 B _2 ]
plot (gini-index-reserve / num-people) / area-of-equality-triangle
& r* f# g7 e' T4 a! W0 D6 _5 X0 Pend
( V$ }+ Y: S; a% j, v4 }1 ^to-report area-of-equality-triangle9 V, E1 @; w4 y: v5 o! r
report (num-people * (num-people - 1) / 2) / (num-people ^ 2)
8 p; G5 w& _! y* aend |