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
$ d# `8 m1 t) ?9 g6 T$ |' K: Nglobals
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max-grain - r. o0 q d. x* C' d
6 F8 N ]) ~- S# O0 T6 _]8 X! R4 I% Z# i8 ~% e3 W4 E
- T: X9 G- `) j0 H% E" {
patches-own% p; B; {. L' F, x
[
& n2 M; ?3 n M. }: A grain-here
0 g6 P) a# f7 w. B5 R# P max-grain-here
3 X0 P& ?* n; @: U0 T O]
3 n3 P# B( ~0 U) `, V
% @# D& [4 {$ `4 E" y8 S' hturtles-own
8 C3 h6 U1 | M4 F3 D8 W' p) e# t; G[/ Y8 @$ u! F; I7 b/ c" g x0 _
age
2 K m7 a: R" J) b; @2 B& G: Y) @ wealth " \& K5 \+ f. c- X% t
life-expectancy
9 T t. I7 _% D9 l metabolism
/ A. T' e( L; d2 ` vision
! I3 _- @* D. i0 q/ i inherited ( W7 V6 A5 H3 d d q- w% i
]
, v0 f; J4 y1 [( [0 Y* k- X/ J& V1 [& _+ x
) { S% K/ F% \
to setup
9 O: J+ ?+ T. x# [$ U ca" q3 {1 @$ g$ k/ k7 _6 D/ f9 T; @
set max-grain 50/ U" Y9 \( M& K% U5 D
setup-patches' H+ Q: {9 a2 s, [; C& E+ X. X1 c7 L/ k0 a
setup-turtles
8 W; S, Z$ S0 a# T Q1 s setup-plots
/ _! j6 R# X9 E& W update-plots
/ k$ c2 P. m& i+ Dend
! {; I5 D5 b0 m G0 z( rto setup-patches
) O) V9 B. R. u- _ ask patches* y6 F0 V+ a" d
[ set max-grain-here 0
5 M2 |' E* p: y# g if (random-float 100.0) <= percent-best-land
" A6 I1 j" x6 C* v' f( c [ set max-grain-here max-grain
4 Z( x4 Q2 w- i! l+ f1 _$ W/ p set grain-here max-grain-here ] ]
8 q, w- R6 t+ z6 @" D5 r: b repeat 5
7 ]6 k/ P& E% a0 e6 `1 x [ ask patches with [max-grain-here != 0]' |9 _4 l) K. S% E# M# b6 h2 ^
[ set grain-here max-grain-here ]
+ o) F* W3 e5 }; J! R7 a' s3 s; G diffuse grain-here 0.5 ]
6 A h+ s% r3 J1 d( u& L repeat 10
& C; \( L* U$ e# t8 _5 D/ Z [ diffuse grain-here 0.5]
8 E# _; y s) D( f% q9 }. S5 b$ T* | ask patches
: k: t) E, K/ e9 S' o5 P9 r [ set grain-here floor grain-here
; X [" y- W8 l( T4 L* c4 B set max-grain-here grain-here " k. H. T+ G, t+ h0 B: W4 x
recolor-patch ]
, N# f# d H: O; Y1 H- o zend. d. k/ ?4 R# y6 |
to recolor-patch
2 z0 x* h+ o m set pcolor scale-color sky grain-here 0 max-grain
, f5 G U0 z% Y/ C; |8 z8 rend" T$ ]3 i ]( z
to setup-turtles. m) m# b/ l( H! a4 U1 x6 Q
set-default-shape turtles "person" f9 E0 M2 N- q y$ y+ F f# y
crt num-people- i% c- V$ m/ V0 w( |# I/ e( f
[ move-to one-of patches
0 F% P3 Z& \* s! e) X set size 1.5 " D8 u& e. @: w# y
set-initial-turtle-vars-age) W; {) ?( S- t0 r% {0 ? L/ s5 f( q
set-initial-turtle-vars-wealth+ `9 b4 d' w0 N: n$ W. V: L6 i
set age random life-expectancy ], c3 P& X. P* v8 }$ S7 ~7 \
recolor-turtles
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to set-initial-turtle-vars-age
) C- p Y ^4 @2 E% m- V) d5 V5 V' J let max-wealth max [wealth] of turtles
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ifelse (wealth <= max-wealth / 3)
- v0 t0 ?: k7 ?% @6 n! v/ i [ set color red + j, Q. ]# b- c0 ]7 S' d
set age 0+ T9 V7 a7 v- ]* Y1 R0 I$ ~9 s( l& d
face one-of neighbors4
& q" l9 W# G8 n set life-expectancy life-expectancy-min +
" l% N7 k& W0 }, ?$ G3 ] random life-expectancy-max . z" {8 \1 W. ^4 Z: M H2 Q1 ]
set metabolism random 1 + metabolism-low" p4 F5 Q+ Q* |* Q
set wealth metabolism + random 302 g: x8 x+ X' s& Y+ k- o. @
set vision 1 + random max-vision* O t. |$ v5 c5 V. `* M
set wealth wealth + Wealth-inherited-low ]
9 C: X1 W4 V, P$ c' N+ m: f [ ifelse (wealth <= (max-wealth * 2 / 3))' F* j$ S' y! Z9 A0 f* q) E
[ set color yellow
4 M8 { C! L; M E* Q+ k set age 01 C6 I; b% R1 S7 b' X: V# ?
face one-of neighbors4 1 m7 h# s; B1 K) Z1 P0 z
set life-expectancy life-expectancy-min +& P" \1 q1 O$ z$ Y7 a
random life-expectancy-max + 1: X3 } a% [6 q0 j0 G* e& m, W" _
set metabolism 1 + random metabolism-mid
( q: P% @7 m5 o" \2 K. s set wealth metabolism + random 30
- M7 u8 |5 U9 u2 ^. B set vision 3 + random max-vision7 [1 d0 c. i( i: |' s2 d# v
set wealth wealth + Wealth-inherited-mid]0 ~) K4 [. p0 X( a4 n8 X$ U2 p
[ set color green
, w# ?1 [* \% c7 a& p U& x set age 0 [$ ~ O8 B1 o6 `5 A- }! c! t' \
face one-of neighbors4 & M/ n1 g d2 x3 S3 Y( M& N
set life-expectancy life-expectancy-min +
Q% C0 N& K0 I( p y random life-expectancy-max + 28 U, ?& |" R! c6 B, g9 d2 J* f
set metabolism 2 + random metabolism-up" T( _( C2 G; ~ T7 t; ]5 K
set wealth metabolism + random 305 E) C; m0 [/ S7 P+ h. |: ~
set vision 3 + random max-vision3 i! J" s2 K* _! V9 o+ `- D% s9 L: m
set wealth wealth + Wealth-inherited-up ] ]
5 D F% ^. a* Q: y 1 T S3 _- b: C" l
end. x$ x: V% P8 P& h5 U
to set-initial-turtle-vars-wealth
8 f, {7 Z: a6 [- ^8 q# u3 l let max-wealth max [wealth] of turtles X7 |% V: T" u- h. W+ g; {
set age 0
# u8 ]8 `2 U) U$ t% w face one-of neighbors4 ) D+ m" B4 R' e J. p d
set life-expectancy life-expectancy-min +
' j5 z7 b2 E3 l random life-expectancy-max
; N' }' C5 k5 ]4 [2 G* B set metabolism 1 + random metabolism-up8 v" F4 W# D1 A3 g
set wealth metabolism + random 30
1 N+ v& p$ r9 |$ C set vision 1 + random max-vision 7 o; m; J$ I! p0 c& o! s6 s9 L
end
! }7 H" ?! L% a' g. [( }to redistribution
, O |$ c; T( ]0 I9 wlet max-wealth max [wealth] of turtles
# F9 [ S+ U2 ~" h9 k& M& q6 blet min-wealth min [wealth] of turtles" t. _4 y b6 I4 [/ K7 f
if (wealth <= max-wealth / 3)
# B- h) B# E, b [set wealth wealth + Low-income-protection ]
% W2 g) w& A+ K: a; ^0 pend
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5 y1 p+ t7 l3 I, ~to recolor-turtles
- X! |1 q( w& D. ^ let max-wealth max [wealth] of turtles
8 g5 S1 J; [/ d/ `! F! p5 t ask turtles
, g' G2 p1 @" O' x$ \3 v4 @& M3 a [ ifelse (wealth <= max-wealth / 3)
. `+ v% m7 ~4 F [ set color red ]
m6 C" M2 ?; ~ [ ifelse (wealth <= (max-wealth * 2 / 3))
2 A8 `7 c* d+ N) ` m. v: l [ set color yellow ]9 D% u5 G! I' `% u
[ set color green ] ] ]
- ^7 ]1 H2 y0 W- ? ask turtles [ifelse show-wealth?
+ |" d4 v" {1 |9 }: a. ] [ set label wealth ]: s' i- K& G5 [# m
[ set label "" ]]. z' a2 D: p& }! |3 m. T
end
+ q4 O6 o2 s. A
8 T9 B: z6 @1 z* p; J, M& Eto go& E* ]6 K" _5 ~* u
ask turtles$ C2 j9 g! U s7 l2 g8 \
[ turn-towards-grain ]
v: |, z9 M! c2 M1 n' B harvest$ v8 H1 X; L; e
ask turtles
9 \; \- Y# D, r* z [ move-eat-age-die ]# L8 R. L+ g' K7 b. R/ a' o6 M
recolor-turtles# Z6 G ^3 g; o. |/ N7 W2 Y
if ticks mod grain-growth-interval = 06 ]% ?: @ T' L% q- p* S
[ ask patches [ grow-grain ] ]
" K O0 r! U6 k/ M- I, e6 M 9 E5 S n1 Q; z% C
if ticks mod 11 = 0
s% P9 g) B1 T% K" j [ask turtles
1 a; ?9 T+ @$ {* } Z7 h [ redistribution ]]2 t: P& O3 o1 Z$ Q
if ticks mod 5 = 0
' K+ u4 w8 Y! g' S/ W [ask turtles. C1 U9 n8 u! G4 S' E
[ visions ]]
: |5 L! A! W4 `7 P1 w. Z tick
/ b5 M0 P/ j- a update-plots! W& K& \& _ _" {$ X% g
end
?! F9 i; E$ T$ A' bto visions Z) n/ A: F3 D6 e1 c5 v7 z
set vision vision + 1
, `% k" _, V6 h2 Yend4 ]: K" ]" f! b) t' a0 u- K
6 \& d9 J0 x, U8 `$ H' L4 q3 j0 t6 l
: N* {% B3 f* x/ q
to turn-towards-grain " J3 g2 c8 H% F5 l' D1 [/ L9 X8 Y m v
set heading 0* d. x& G. N- Y) O1 M/ X$ T
let best-direction 0
: V, z& @8 Y8 s( L0 @/ _ let best-amount grain-ahead( \2 }: s3 z1 D% N7 \4 U' W' r
set heading 905 W1 a& a6 _) Q
if (grain-ahead > best-amount)
$ R- m& M$ J4 p/ a' T [ set best-direction 90
?0 |! `% I" e3 q# [ set best-amount grain-ahead ]
: n; y; K, x- M0 l$ @1 j; L, Q set heading 1806 k! K' ^+ [) C$ h
if (grain-ahead > best-amount)
* i0 |. e! I5 O; _% e [ set best-direction 180
: r5 {: u3 W' u& E set best-amount grain-ahead ]
( {4 Y" j3 u# Y set heading 270
/ B# b* ]" {" W( A if (grain-ahead > best-amount)
1 r2 T4 K) m- G" ]8 m1 s [ set best-direction 270
% q( Q! S9 R# f2 D/ d set best-amount grain-ahead ]+ A" n" V$ S! W5 t* F- |
set heading best-direction }: |0 z Y$ n& j" _0 J
end& y) ]" }+ e% D; F
; J' h/ [( s( }: e0 j* r
7 P+ R8 }, \4 c; b$ Yto-report grain-ahead 8 q$ L1 \$ h; {8 l$ o+ c
let total 0
, R) _6 [ |/ y) K" K. ^: t0 R let how-far 1
8 H4 `( T* V0 e. Y0 h repeat vision
* K7 E( [ W; w' S1 y- ^0 y [ set total total + [grain-here] of patch-ahead how-far5 W* z4 a6 G. E! h
set how-far how-far + 1 ]
* w) {/ L) J5 z! p report total
) q' I, Y* f. Zend
3 U% ] \9 }% a y0 O
2 B; m. T1 l# G8 Ato grow-grain ! y6 A( }% N! ?8 b
if (grain-here < max-grain-here)
, D3 ], s& v! ~( s# } [ set grain-here grain-here + num-grain-grown3 {" Y( c7 E/ b5 S) C9 b
if (grain-here > max-grain-here) + P* ] B, B$ x9 ]+ y' r1 {; N
[ set grain-here max-grain-here ]
# i' d% F% B+ ?( r$ J+ b0 F/ f8 f# B recolor-patch ]9 t; i* I: S& _5 d6 h Z
end
' t( m, W! _1 E& [+ b- i) zto harvest
- o, j6 ?6 G; f+ P X$ ~ ask turtles
0 A) M0 Q9 V8 c: x, C [ set wealth floor (wealth + (grain-here / (count turtles-here))) ]
4 P; ~5 h5 O- O; S9 D1 N! x ask turtles9 b2 y. z! t) S* A4 C+ n6 |# V
[ set grain-here 02 c" z- D. j: G; e- W2 c
recolor-patch ]. Z5 F/ ]' o0 g
0 M3 f% n* V* {5 { p: Iend5 t% g# M2 J% B/ x
4 }7 M K% `- a+ K8 X* Y
to move-eat-age-die + i w, p/ z6 N6 L% ]# `
fd 1$ A2 u* i! L$ d! |
set wealth (wealth - metabolism)$ @/ O C. n Z" \$ S
set age (age + 1)# s5 i: Y, Z. E% _: u
if (age >= life-expectancy)# n7 S7 i% L% e" N1 I6 e
[ set-initial-turtle-vars-age ]" C8 S2 S0 n# `4 y# `
if (wealth < 0)8 ]% w3 Z+ h8 {) T+ L0 ~
[ set-initial-turtle-vars-wealth ]
* _3 @8 E F9 q
! D6 F6 x% z9 E- pend. ^ d# p c+ p& }+ J
1 o+ u V8 F6 x+ {$ o
4 Z+ [7 f/ Z3 I0 N7 F1 p
to setup-plots
# r4 y- v( \* ]& m set-current-plot "Class Plot"
/ W: C* r8 E v set-plot-y-range 0 num-people
4 n" A6 P- Y2 L4 H0 d8 c set-current-plot "Class Histogram"
9 e2 J$ Z6 Z: u1 e7 @( Q4 Z set-plot-y-range 0 num-people( J; q) y! H0 Z/ |( t8 N5 q" I
end
2 s4 v1 ?- F( [& {! ~' L4 x5 U+ r( @9 h- A- }# L# v2 ^ q
to update-plots
" c; d* v% |, \3 Y1 C% a. p update-class-plot
) i* P M% I d update-class-histogram
+ l0 j: q$ P% O# u8 b update-lorenz-and-gini-plots
1 A- v* r' @* K3 Q* J V$ z6 X* T: Lend
: |% t! b/ r' s* {( o
+ Y; E3 y; N' T. i d' Uto update-class-plot7 y- F) ~2 y) E" ^# L' t# b, J
set-current-plot "Class Plot"" f8 m6 @( X A+ W
set-current-plot-pen "low"7 W" ]7 f3 c i* v8 r
plot count turtles with [color = red]( c0 Z0 t+ W' S) e \' s( K
set-current-plot-pen "mid"0 D. l# i! n" L+ }) O5 m
plot count turtles with [color = yellow]/ }' ~; d2 e7 i5 y) ^5 S( {$ R. x( O+ S
set-current-plot-pen "up"9 ~. ?% M6 \" @) `( Y) d8 w
plot count turtles with [color = green], M1 Z* J+ ~3 S7 U7 O4 |
end
2 O2 e% s4 e$ b
" B7 C4 `! f( y1 F$ ]$ s; I! v4 Lto update-class-histogram* l' T; L9 b' b5 s8 k
set-current-plot "Class Histogram"
$ P# r* r- [- d0 X8 i5 } plot-pen-reset7 `) _1 P" m: d* J
set-plot-pen-color red
. n! N$ U4 S0 B, u: p8 m" O plot count turtles with [color = red]& H1 C7 r6 R s
set-plot-pen-color yellow
_/ Q( p5 X- ~* V% V% S( H: T plot count turtles with [color = yellow]: Q/ |# A& x% U: S/ d. g
set-plot-pen-color green
. [: |4 C( x: L+ F- @# ~- R plot count turtles with [color = green]
7 }& I! Q# w5 ^; Qend
7 h. e) {7 `# `. v) Wto update-lorenz-and-gini-plots
3 L+ @( q) Z4 Q& w0 z. z set-current-plot "Lorenz Curve"
6 _# ^, V' u" O2 m clear-plot" o+ a8 a4 J4 a! G3 F+ h
9 Q% s9 O1 l. h q4 A7 k- `
set-current-plot-pen "equal"
2 [4 W" a& I2 H: g plot 0( w' h. C. R6 L4 a' S, e. ?6 x
plot 100+ @5 B0 d5 U0 p; q0 t
. [! l0 M1 e, u6 f9 D2 Y) ?, A
set-current-plot-pen "lorenz"0 z1 w* |* E' ^3 j
set-plot-pen-interval 100 / num-people+ r. Y) s3 ]! U( s! d7 _6 i
plot 0
" @+ f8 \% N5 Q8 G1 K% d" W$ ]! S8 l0 b
let sorted-wealths sort [wealth] of turtles
( [$ U* f, V& d0 w' G# I% y4 P let total-wealth sum sorted-wealths
7 D9 {. H" y$ u; N! V6 d; p8 F let wealth-sum-so-far 0
9 w. T- j+ l& s- z, T& q- m. J let index 0
, b0 M4 E n* j5 S let gini-index-reserve 08 u: F2 k# G$ p. q
h$ ]9 Z* S! u o repeat num-people [
, {" Y" t0 u9 V+ }& a( | set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)6 \- _! E0 O! j$ _# E( v
plot (wealth-sum-so-far / total-wealth) * 1009 a1 f u+ J2 M! d& O
set index (index + 1)
0 M7 L1 K' T3 ` S3 r0 \( `" n set gini-index-reserve6 U' D. z/ c. J9 R Y
gini-index-reserve +, H, h) E, O! m K& l( T6 v
(index / num-people) -* p3 w9 I$ A+ P0 v" @
(wealth-sum-so-far / total-wealth)' a9 O* n* C; c7 Q) z1 F& f
]* m% [) @5 X) Y. j) D
+ j; Z1 j; M9 ^4 u( }6 d2 c* g set-current-plot "Gini-Index v. Time"
" Y+ ]$ d: D0 |4 f0 G8 j% ], Q# ^ plot (gini-index-reserve / num-people) / area-of-equality-triangle
1 I% O6 F# y# Y V' q: ^/ B% Eend
( j( A/ a& X0 j ^to-report area-of-equality-triangle5 x5 ~6 ~. J* W
report (num-people * (num-people - 1) / 2) / (num-people ^ 2)3 H2 u) `/ `& E
end |