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
0 n1 q+ H- ?4 ?% a% E; \globals0 A' R t' E" f
[. W, Q8 q9 [5 V( V' Z
max-grain ; t- ~% p. y: N
3 h. j4 S# }6 k1 h. N
]
5 b' M5 Y" @- R: Y0 W/ e' E0 i6 x+ a2 q; s' G
patches-own r# H& ?7 o9 p: s+ h& Z J
[
: Z. F& ^% Q: g/ \ grain-here
7 v- q. @5 A' i2 `0 f6 a max-grain-here # F7 b! O( q' T( r- @
]
4 |1 T! n! K$ k7 k: [
% Z% M+ l' }& K* {2 K" Wturtles-own
. {0 T" O% I. ^8 H- A- ~! b7 p" @% P) X[$ ~! x y/ n: N2 n' ]# R: @4 S
age " ?# t; m* G2 p* x
wealth
* b2 ]3 M) @0 R1 A( r9 K5 r+ M life-expectancy
5 |. @9 ?4 u. {; }9 R) I# c- [# R metabolism * B9 T8 j0 h. l' [
vision
# x, y! B; G+ A' z" x4 B& Q; I inherited 8 ]- [2 I& k, b) _$ B- t5 T
]2 j8 D7 C' L. P# L' o( u: L
% F: F$ U* J& `
3 W; t7 B+ d5 w9 zto setup0 V. L/ z& {7 ?! H" M8 P# h" q3 n& }$ W
ca: j4 e6 N7 o! I, ~5 Y
set max-grain 50; A- P; P0 R& ~! @7 I1 H. f
setup-patches- g. R* l8 m# h2 p! A: J
setup-turtles& w- c- k2 F" b; s
setup-plots
% i- p5 z" X! x update-plots# m' ^ @ p8 ]* \+ o
end
; o" ?, B, _( q/ Y" g+ _4 C3 hto setup-patches/ l3 b8 \ k! l' e- ^ d
ask patches
1 @1 a4 Q" f: F( D2 J# h+ A$ D [ set max-grain-here 00 B7 F9 `. v% d* u& E
if (random-float 100.0) <= percent-best-land
! W# M$ W& Y3 U( N$ U8 X w [ set max-grain-here max-grain/ C6 G0 {% m$ P6 G# k
set grain-here max-grain-here ] ]
' k' ~" |$ ~5 k# t, i( L) M: I repeat 5& V8 S* i4 n! x+ y* G
[ ask patches with [max-grain-here != 0]
. X1 e8 m3 ?% e! w+ w- E+ X [ set grain-here max-grain-here ]+ p% e& {. v! {& z% r# y' l. G
diffuse grain-here 0.5 ]
b; J1 Z4 ]7 Z$ Q repeat 10" S6 Q* y" C( G
[ diffuse grain-here 0.5] ) J1 i" W X8 R: n
ask patches
4 B: J! F; Z; `0 s' g6 m" Z3 R [ set grain-here floor grain-here
3 a) B7 K3 W; ?. o: A6 U k5 Q set max-grain-here grain-here
; n! p, o4 ^3 U; Q3 V ^' y8 e+ w) G recolor-patch ]
8 s/ q" P9 T6 b, I- Y4 w6 Send$ o& N9 T. ^* Y/ F
to recolor-patch 6 J# ^: I" B$ M% D6 S8 z4 E: ?
set pcolor scale-color sky grain-here 0 max-grain
" ^; d7 J. U( [' S: Send
( g5 b" f) ~; i: ], W8 s5 rto setup-turtles" I/ y9 E9 A& y4 j
set-default-shape turtles "person"& u& O) O( n' w) x
crt num-people. {( T1 Z6 v" p* h, }% [
[ move-to one-of patches
' T. p& U, V% N/ {) \8 { set size 1.5 / n3 Z# U/ ?# n t
set-initial-turtle-vars-age* M7 m" @7 ~3 s, H1 L h! h/ N
set-initial-turtle-vars-wealth
, C6 x0 G4 G2 D( J( [1 d$ s; ?- @: n set age random life-expectancy ]
* |* z) x. v3 t9 ~2 K/ `9 x recolor-turtles( @1 y$ K/ B, n( o% p
end
1 s g" ^ e2 O# G3 D( E, t' v
* x0 K( P. G! x! r1 q/ Uto set-initial-turtle-vars-age
3 o: u! f4 @. z let max-wealth max [wealth] of turtles
( K2 H5 k) J% k- D * p$ z: r" m+ r2 _" R. H1 }, p
ifelse (wealth <= max-wealth / 3)5 f- e8 y+ s5 E( p0 T
[ set color red
% }5 ^* v; Z+ N9 G( Y set age 0
) S! z9 j# E h4 d, ` face one-of neighbors4
& Y" n; z+ \ s set life-expectancy life-expectancy-min +
2 A2 g4 Q4 e" D3 j/ V random life-expectancy-max ( j# ~6 E) l! T0 a1 ?/ x1 w, R
set metabolism random 1 + metabolism-low
7 u$ x: l( a( L) p$ q set wealth metabolism + random 301 |& @- @+ p- ^! o" a6 Q
set vision 1 + random max-vision
6 o& M! T, l3 _9 k' l' @" u, y3 D4 W* M- j set wealth wealth + Wealth-inherited-low ]4 c" U/ {$ } _) U9 p* \+ r7 M' C# A
[ ifelse (wealth <= (max-wealth * 2 / 3))( K D& E& ]; Q# L( d$ m
[ set color yellow
. A0 b) {* R) p3 i& d set age 07 b# d8 `4 g8 G- c. }
face one-of neighbors4
* f5 N4 h0 V4 V set life-expectancy life-expectancy-min +) ~" h5 F$ H& t `, [6 U& c3 M
random life-expectancy-max + 15 d' u7 v; @0 c% a) R
set metabolism 1 + random metabolism-mid
) \9 H0 U0 U7 L+ f6 E- B) M set wealth metabolism + random 30
, a6 a! \2 Z- O set vision 3 + random max-vision8 p) Y0 Y2 S6 h, E4 r$ l5 `
set wealth wealth + Wealth-inherited-mid]$ ]" ?& F$ d$ @4 d
[ set color green / `) U5 b4 n! s c; p
set age 0
; ^# O2 o/ o0 N! n% O0 } face one-of neighbors4 4 i; [6 a+ P) X+ D
set life-expectancy life-expectancy-min +1 G9 A4 \7 ?9 l. j* E
random life-expectancy-max + 2+ K* Z9 ]; r' e% A: y7 @
set metabolism 2 + random metabolism-up) F1 E6 G. C4 g, f5 [
set wealth metabolism + random 30; s$ V1 N9 H, u. T) i, S" v
set vision 3 + random max-vision
o* ]/ l6 V9 X" R* u8 S( J5 z set wealth wealth + Wealth-inherited-up ] ]
5 |8 K/ l5 z: o& R" T: I: p
& q/ X8 ^& l2 K% b7 j) [: Gend
7 ~7 T8 K1 V& `* [! Q( Eto set-initial-turtle-vars-wealth& F, b' ?* |, c3 @
let max-wealth max [wealth] of turtles% b5 h$ p' J8 P6 L8 G6 s+ [. c* K% G! }
set age 0
9 [" P4 h$ {8 w; f face one-of neighbors4 ( N7 l8 v4 X2 x* z9 L
set life-expectancy life-expectancy-min +9 } i* O9 B* Y' j- e
random life-expectancy-max
: v! J8 b3 l3 }7 q, M { set metabolism 1 + random metabolism-up
6 j' O( r3 ^' S set wealth metabolism + random 30! V8 b4 f% ^ f1 V
set vision 1 + random max-vision - _- c+ o! `, V) s" z1 b5 u1 X
end& |% m1 y% _$ R/ Y" M9 x+ V
to redistribution3 t3 f6 c! T+ y4 m
let max-wealth max [wealth] of turtles$ M3 g& }& ^ f1 D. y0 g2 I& W
let min-wealth min [wealth] of turtles
U8 N' K8 \$ f5 qif (wealth <= max-wealth / 3) p+ @1 K2 @; e% E6 b
[set wealth wealth + Low-income-protection ]% O9 y/ K/ r Z5 u" N
end- b3 F% Z- N5 E& g0 d9 B7 Q( K7 n7 p
* T3 i2 B) n4 ^! N( J/ t8 T
to recolor-turtles
0 s$ `# i; x5 Z* x/ W0 A4 j2 u' b let max-wealth max [wealth] of turtles9 z$ A8 z' @' W2 |
ask turtles
' F: R ?" H: h! Y9 y [ ifelse (wealth <= max-wealth / 3)
5 E" Z" w2 h3 X2 B [ set color red ]- z3 P$ u8 s! M# p- `
[ ifelse (wealth <= (max-wealth * 2 / 3))
; x1 |6 `/ ], I4 g% R& q1 O+ f2 i [ set color yellow ]/ S* Q k' A: W# B6 Z$ g
[ set color green ] ] ]$ f3 @+ R( _' Z$ c* g+ J2 s9 Q# ~
ask turtles [ifelse show-wealth?
+ ^2 G) ?" I# w: x [ set label wealth ]
( n3 ?3 m8 P1 w2 F8 r3 { [ set label "" ]]
: E0 a+ V4 T# s1 l% A$ p, ^2 B7 G7 wend% _2 q5 V. V: o! U$ c, f
' w; E. Z3 `( o {* r, M) t; t& a
to go
; E+ e+ L1 f/ Y, H' E9 ` ask turtles9 p, h2 T! x! p6 @! S$ p' A' y1 \
[ turn-towards-grain ]
3 c5 _5 t- X, \# F- r% v harvest1 I l8 V9 B+ S. m3 A! D1 e
ask turtles: F& o7 b/ c V' X5 h1 `5 Y$ w
[ move-eat-age-die ]0 x' B, x: [5 X X
recolor-turtles/ Y# C9 \" a! K7 i
if ticks mod grain-growth-interval = 0
8 x& l: Z# _0 T4 |5 y0 z [ ask patches [ grow-grain ] ]" g3 i4 i: l$ N0 q5 ^' l
' ^1 P# ]' T- g3 a) N if ticks mod 11 = 0( q* _+ {( j/ h: Q; X& {7 S
[ask turtles( I- g8 H7 @% C$ `7 |) Z, e
[ redistribution ]]
+ A( E; T8 l5 t! g8 k. E9 e if ticks mod 5 = 0$ \5 `0 N4 @% W% S6 c
[ask turtles
1 U4 O7 w- |6 [ L6 |- T( t" }9 k- s [ visions ]]- l5 }! k2 c \6 E9 g
tick
% o) a3 b0 ]& l0 ^0 H5 g, ?3 G update-plots' `1 f, I3 R. Q( x" U
end: e' | ]) R- R' z, R. M
to visions/ S7 ?. n6 G% y% ]0 ^- [+ x
set vision vision + 1
7 J/ v' Z) }$ u* e& V- Xend
, q8 g" k. {- n$ } t/ }5 o* b) |1 G" N1 O0 O) x4 u& E7 f
3 B! ^% b$ k3 M) v: h
1 T* j6 k$ k0 `# c7 A7 q1 @; c; jto turn-towards-grain
' \" } M; y% K# y- D Q set heading 0
' z$ `# _5 W% \ Y) G; ? let best-direction 0
$ o6 |: f! y8 ] let best-amount grain-ahead
2 o4 E3 S0 u! P1 Z. Z" N set heading 907 G* G; c9 Y5 z n
if (grain-ahead > best-amount)
( w: j! z8 u' N t/ `# H1 M: f4 y [ set best-direction 90
( E/ m% L2 Q2 a) ]$ V1 j set best-amount grain-ahead ], ~' k* x' g. ~) A) v6 Q# ^! }4 |
set heading 1804 ^9 B; y H( v, ?* N9 d0 a, T
if (grain-ahead > best-amount)
- K9 ~: L- I/ F [ set best-direction 180
; x; @. S) ~# f4 f1 F set best-amount grain-ahead ]2 P# ^4 C7 o+ @4 l. @7 i5 f
set heading 270% F B, }& H$ \' \3 N3 s# v4 G: V
if (grain-ahead > best-amount)/ c0 }6 i$ k. x# I) A2 d4 h
[ set best-direction 270- _- G4 U' B% W: u
set best-amount grain-ahead ]: f* r2 Z+ x6 K4 }6 W9 @/ P
set heading best-direction$ @. B' ^4 q. w3 J+ r8 e' @
end x( w, M9 P# i" e% `
, D q2 ?1 U/ _7 x Z9 R
Z. ^; W) D8 W |
to-report grain-ahead ) i) E' r- Z' n
let total 0: e- T7 ?* @ j' r8 p" S( r
let how-far 1
0 S7 U+ A% x- K; v; ?/ P, R5 e+ m repeat vision
4 ]7 ^# _ Y7 x [ set total total + [grain-here] of patch-ahead how-far0 x7 K9 y( @; l. k+ l
set how-far how-far + 1 ]: ?3 C: K- i% b. A; W/ e
report total+ e c$ E* @% Y% H. U
end
0 o; _2 _) t% f+ U( |
. z0 r9 y4 m5 m- l" Xto grow-grain ( N& t# g* q* }# G9 d, q& M' P4 `
if (grain-here < max-grain-here)2 g6 c ]) `6 q5 R
[ set grain-here grain-here + num-grain-grown
* V$ `( B2 r3 c F0 T7 J if (grain-here > max-grain-here) ) `4 h, c M0 E& y: S
[ set grain-here max-grain-here ]
$ L# ^' i8 S; U recolor-patch ]
4 X' B' H! P- d) d+ V2 g4 zend
* R y0 U5 n' L+ Y+ }( p* Q0 Uto harvest
9 w- b8 g/ ~2 x% e4 p ask turtles
+ Y. a8 b- a4 O& w4 Z$ V1 G [ set wealth floor (wealth + (grain-here / (count turtles-here))) ]
! U, F. Z9 i3 l* {3 r4 K" A ask turtles7 q; N/ v+ m# H
[ set grain-here 0
1 ^6 a5 H4 \: X% E- K9 M+ P recolor-patch ]3 f3 g, n4 N) w9 M2 D8 d4 z5 l
; o# c% L* Y7 [! \/ |+ y
end
0 ~8 o( o& n: L3 K" @% D
: T7 [: c+ t1 |to move-eat-age-die
* B" L1 i+ z+ A fd 10 g) n3 g8 e( e* q
set wealth (wealth - metabolism)/ E9 O: j! n7 a' `
set age (age + 1)
7 m; E6 B& I/ y S) J" C if (age >= life-expectancy)9 R. T j: n' L* w- O' D! m
[ set-initial-turtle-vars-age ]
( ?5 \% T( h4 V) F$ v1 V+ [* ^* o if (wealth < 0), D" ~6 K3 h, S+ g* m! Y3 B
[ set-initial-turtle-vars-wealth ]
3 f* i; N1 ?6 @, d" q7 e/ a # ~: f3 t6 P2 l
end
3 J3 v( h/ B" ~' k% V7 J' Y- p8 X
) Z! J Y: Q: h$ c: k: t; j4 J
/ K/ G% X( J4 O3 ?5 l3 H4 j$ ato setup-plots
( P Z4 |' `9 v# t! @7 O5 h6 N set-current-plot "Class Plot"
9 D& _# g8 s5 K5 E set-plot-y-range 0 num-people
! q3 x1 b( }7 T& s' S7 }; I set-current-plot "Class Histogram") `6 ^: j) v4 y7 Z
set-plot-y-range 0 num-people
3 x5 @+ q1 ~* ?: v% dend7 `3 T. c: h9 L d( M5 k3 ^! B
4 ], p( R/ f, j. Uto update-plots* y! w- _7 U% X$ _3 {2 e
update-class-plot
6 I. ^ O4 i7 _ update-class-histogram
5 N! b: j. L5 W( O( V" A( N) [ update-lorenz-and-gini-plots
6 _5 p( ~) v* h. F+ u: T; }% Fend) H4 }) h9 l3 T+ q! u
3 M" m" J- I7 W
to update-class-plot
% Z1 z3 E1 F o& ~; ] set-current-plot "Class Plot"
2 Y9 ^, a6 c- o set-current-plot-pen "low"
: h* O+ I7 K; f6 N( O8 Z" s8 k F plot count turtles with [color = red]* o; `3 N7 `) G5 ?" B% r
set-current-plot-pen "mid"
$ C7 q5 l! _% U plot count turtles with [color = yellow]
, Y! |) k. H3 Q) g8 o set-current-plot-pen "up"
9 n. U( J3 Z9 g plot count turtles with [color = green]
; U! L J7 f) ~$ Xend) L% k" P0 D- ]. x
+ ?' e: w# Z. m! T& J5 v% u2 zto update-class-histogram7 [8 T G' P+ I7 g5 Z3 v6 H
set-current-plot "Class Histogram"6 z# j: T+ t: N) T8 M
plot-pen-reset1 _) [/ Y6 s" p) ~* h
set-plot-pen-color red
8 u1 {3 ]: [6 p. b5 X5 l plot count turtles with [color = red]& n4 r0 S5 Z' \$ \% Y+ q6 g
set-plot-pen-color yellow
6 D* Z! L% \) O2 b& T plot count turtles with [color = yellow]
' ~4 Y/ L4 B" r4 U: Y set-plot-pen-color green
5 {7 j4 A/ z0 a- g" Z. f plot count turtles with [color = green]
9 R5 g# W$ R7 R% o( n, W B: cend
+ p* O- l2 ~2 y* O. Wto update-lorenz-and-gini-plots! V8 U9 R5 _' p) P
set-current-plot "Lorenz Curve"/ Z0 C; B$ |8 y) I/ o$ P9 o
clear-plot1 d8 f3 c& {4 u' d# [
& u7 A) S4 D" W# D a. |/ V
set-current-plot-pen "equal"
; K; g, j6 r: b0 N) l plot 0
/ D8 F& v% _3 i plot 100
: F/ d1 U' E N7 c; _# r" k% |, g. O3 m+ L5 m
set-current-plot-pen "lorenz"
1 h6 L& |% v1 Z6 Z. f set-plot-pen-interval 100 / num-people4 F e- t% N5 k% o8 o2 o
plot 08 _3 `/ B# |. M+ |" k/ ~
! |7 Y4 g( m8 U2 S let sorted-wealths sort [wealth] of turtles
* \: k3 ]( Z% C' Q3 x/ E let total-wealth sum sorted-wealths7 }$ P* S, J; n1 _4 E' z% N; E
let wealth-sum-so-far 0% {2 z8 P4 D# K% J/ G
let index 0
6 C# C3 a4 ]$ ~' L+ n8 v- ^2 c! f- { let gini-index-reserve 0( V) @6 u2 j6 E( n
+ t) E- C4 I' L repeat num-people [7 O) _& d# X- F0 D7 C/ v4 Z
set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)
4 m" h$ f* ]% I3 S8 e plot (wealth-sum-so-far / total-wealth) * 1004 Q' [% W+ c, ^- M
set index (index + 1): J+ [- Y \# Q1 W
set gini-index-reserve
: x+ [; W% N" X0 H gini-index-reserve +
7 e! W) X& a0 p, K9 ~7 ^( Q (index / num-people) -
, c$ Z0 K2 T% T; i+ A (wealth-sum-so-far / total-wealth)! W7 r5 K4 Z: C7 X- B# q* M* w/ S
]% Z; a6 ` X+ [2 \$ H* ~0 I! k
9 p0 q4 d+ m6 J( u% Q
set-current-plot "Gini-Index v. Time"
& o% p6 q0 A/ S3 U$ T4 W plot (gini-index-reserve / num-people) / area-of-equality-triangle* O$ t% W n; ?. v8 H* M* m3 T
end
7 }) {2 T5 {# d& x% F7 c& x$ dto-report area-of-equality-triangle
$ z( L) F1 @4 _$ c8 }7 X report (num-people * (num-people - 1) / 2) / (num-people ^ 2)/ s4 x: A' _ i w
end |