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
" B2 V. ~. o* U$ y' B3 I0 x! ~ hglobals: r3 k6 P( m& a' L! L5 v
[
, O. L( {/ R" L& w max-grain
* d6 k" z) P6 @5 b! l/ r4 _# J3 T: z3 F, f& m, V% I* A
]% X& c! q1 J$ }! O4 X& H9 ^
/ ?2 [. @ f5 j
patches-own% P9 j; d+ @) ~9 G
[/ L% R0 ?+ a# n( R3 k
grain-here
% X7 [0 d1 o3 _ max-grain-here ! d8 v) P' c; [' z) E- z
]
. X6 R( H! x9 V+ @5 ~) G. ^% I" D! N# @2 m Q' \5 y* q( ^
turtles-own) P7 o, a: k. {& \2 b8 w) X
[$ t' p7 ?/ d" y: D6 O
age
: _1 p- Z, j( R) z6 P4 B; M wealth [2 ?6 b7 z, d% }/ E7 t4 X
life-expectancy ( B7 X- b1 ]: m+ r2 P- P/ g! T
metabolism
( j3 I% c3 V: K) \) w0 J6 | vision0 l7 K: K& C' r( s+ X- N9 a; S
inherited ; Y( F" D3 X3 {* b I+ ~' {) N
]
5 k8 j* I+ I! N/ V1 p4 l, e9 H9 d2 s% z: p- y# {" D
" I. l* _. u) _: L1 y6 T$ J
to setup- J+ @, m* ~: W- K
ca! i- _4 i$ {2 P% E W
set max-grain 508 I* r5 \, L, C
setup-patches6 r/ Z4 |2 O9 I+ p5 k; R/ I2 y% [
setup-turtles
! i: ?% `* k3 b. s i- \ setup-plots% @- _ t& V9 B2 E
update-plots) Q! p3 G0 y% g: N4 ^
end
* D) n; }8 w9 R7 p- wto setup-patches. s) l$ Y% U2 n7 q" U2 G
ask patches8 o+ g5 z) J4 M* M- {
[ set max-grain-here 0
& {6 E) @3 y1 M; H, U if (random-float 100.0) <= percent-best-land- \7 C8 ?0 u3 l9 M
[ set max-grain-here max-grain! g4 a2 V; C; n8 s3 n! }% ~4 @
set grain-here max-grain-here ] ]
& L% K( T' @6 N7 g d- p- P( E repeat 5( E. J! s' i+ M5 j
[ ask patches with [max-grain-here != 0]
# M8 ^8 ^7 l7 E0 E [ set grain-here max-grain-here ]3 t5 ~/ i# t1 c
diffuse grain-here 0.5 ]8 s5 I; ]2 }" A4 t( ~2 o! r
repeat 10
0 v7 k4 w" J ^ [ diffuse grain-here 0.5] & X+ o, I# A7 L* g: W" _
ask patches2 T7 Y+ F" i: }8 L9 A( @; G
[ set grain-here floor grain-here
7 m/ _8 u; l+ B! N2 A+ U set max-grain-here grain-here ( k$ {+ O0 z9 C! y" J4 Y2 V) b3 O
recolor-patch ]9 a3 m$ E, F/ _" W
end C: A& x. z* X: N& I
to recolor-patch 3 p# e. k R$ f! k& @5 R
set pcolor scale-color sky grain-here 0 max-grain! w1 a# c2 v2 l1 O
end) b- d. S8 C9 [; K+ N
to setup-turtles
2 k* ^7 w& D' O. a7 B set-default-shape turtles "person"
) E% }* W- Z# Q" ~1 v9 `) H: I crt num-people
5 m: y- [1 K4 ]2 V0 T9 _ [ move-to one-of patches ) \' y4 L- R1 D6 m& W t1 Z
set size 1.5 # Y6 M$ E1 k3 j- z! k5 O2 J9 |
set-initial-turtle-vars-age% I2 @! ^ d c7 _6 L7 ]( ?0 v
set-initial-turtle-vars-wealth
% c$ M+ h) f% s; q9 \ set age random life-expectancy ]
' f5 U, N7 O/ ]+ g# `3 l recolor-turtles
3 `" `- v/ \' R$ G- T, Fend! W, u& B3 L: L, x" R7 k7 D; `
: o8 U6 U" H8 s. k$ Dto set-initial-turtle-vars-age8 L' v( B* h2 V. D# G" `# l
let max-wealth max [wealth] of turtles
7 k( c5 B. |5 d; K- z
5 A, Q7 a1 ?- _% a w4 x7 [2 i: f, u ifelse (wealth <= max-wealth / 3)
' E# _3 }0 G- G4 y" k/ G% p5 T [ set color red
( L3 v3 v( p& n set age 0
! I& F: c9 S c' E9 ?6 N face one-of neighbors4
y, u$ G9 c( N. g% I set life-expectancy life-expectancy-min +
% r$ h! v3 s1 b" \ b% s" Z/ g4 H random life-expectancy-max . Q$ [) G, I, X7 P7 S
set metabolism random 1 + metabolism-low
3 Z1 F! H5 E' j. j1 M+ \8 L( g set wealth metabolism + random 30
. F) j7 K& t! I# x+ R set vision 1 + random max-vision& c+ _) i+ Z: a! R+ U* p( A6 ?
set wealth wealth + Wealth-inherited-low ]! |( M. H% ~6 G* ?: l. p) f
[ ifelse (wealth <= (max-wealth * 2 / 3))% o6 A; w, Z$ y( g) i
[ set color yellow & B6 u* v( f8 U+ i" P9 G7 |9 M
set age 0
4 l% ?3 |8 |! J3 F: x6 B) Y- C( X, r face one-of neighbors4 9 s: Z4 ?! V) j, r3 ?+ Z: J- \. M
set life-expectancy life-expectancy-min +
" [: o6 I# |% D* l" t random life-expectancy-max + 15 l; g* z7 I5 o5 P& W
set metabolism 1 + random metabolism-mid. O3 ^/ I9 f; ]' F+ f) Q# [
set wealth metabolism + random 307 i5 C% b1 O5 o3 C l
set vision 3 + random max-vision8 e( @' V1 _- i8 u, c- h
set wealth wealth + Wealth-inherited-mid]. Y6 G0 P8 a9 L
[ set color green
5 P% W& ~1 Y* I! J$ l set age 0
) S, a; a( ^, B face one-of neighbors4
; s/ `0 E4 b) E2 S0 v set life-expectancy life-expectancy-min +0 [+ @! p! `. Q" F( v0 F6 a
random life-expectancy-max + 2
1 G4 D9 r2 o3 S4 i% G( u' V/ J# L set metabolism 2 + random metabolism-up$ E% s% G9 V8 x/ o: `6 V' B2 m3 V6 V
set wealth metabolism + random 30$ `$ C$ o, E: O1 S
set vision 3 + random max-vision
& F2 n$ A0 ]4 W: m1 q set wealth wealth + Wealth-inherited-up ] ] 0 M9 K5 q# E- m+ x
" y9 c; K" t# O0 Eend
6 A7 S6 h+ P- w( ]; O4 p+ q6 yto set-initial-turtle-vars-wealth
H3 G2 b2 m+ R! P let max-wealth max [wealth] of turtles
. d* Y) ?/ [9 H. J3 r set age 0
4 f/ R; H7 K' u4 D F8 J face one-of neighbors4 c) f5 m; E. ]9 N% e
set life-expectancy life-expectancy-min +
: e7 S- e* p" b: ~4 x random life-expectancy-max
3 Y4 T8 U& U; `5 O5 v set metabolism 1 + random metabolism-up
/ T% [. Z u7 b1 q4 t- r2 V6 j) H set wealth metabolism + random 30, `3 }% \# r1 i: ?) F
set vision 1 + random max-vision 9 p9 F# U2 E/ h9 I3 r H5 S% I
end |0 r# K: A2 z. l% S" X! a E
to redistribution5 \- r* Y, k# E8 j* O) M) P e; ]
let max-wealth max [wealth] of turtles8 e- a: a* _" I4 `
let min-wealth min [wealth] of turtles- K, ~4 f- L) v* D4 o1 d* D% ] H( l
if (wealth <= max-wealth / 3)/ f" U/ H. |% j' f5 ^
[set wealth wealth + Low-income-protection ]
% G1 t: \8 H# e( Mend
% x2 e y I( y5 d 0 @# \; y7 V# p n: f
to recolor-turtles
4 A, X7 D/ h3 A let max-wealth max [wealth] of turtles5 y2 n; r7 |4 A: M$ j2 Q7 f. u
ask turtles6 h9 d" F! |+ k
[ ifelse (wealth <= max-wealth / 3)
9 E7 l0 H- G |) x0 M [ set color red ]8 w. Q+ F$ k$ H8 E; c
[ ifelse (wealth <= (max-wealth * 2 / 3))% a6 a+ A4 P1 P/ n4 C2 q' _/ ?
[ set color yellow ]
$ {( O3 b% z9 ?: N1 S [ set color green ] ] ]
6 Q4 j. W' a* U3 I+ Q# ^: n( ^ ask turtles [ifelse show-wealth?
( o2 m$ n" q* L7 s [ set label wealth ]4 O2 C( t( ]. j' p" V1 O0 q' W
[ set label "" ]]3 }7 u( C0 P9 H, m/ Y
end3 j2 ^0 j* \1 Z; Z$ ~; r6 x; J) z- g7 i
9 @ ^4 V7 A+ R; B# {* O; t
to go7 y# o# q; X2 M9 [4 @
ask turtles! @# n, \3 c2 W; o3 e' ^" F
[ turn-towards-grain ] " ^# i2 l5 {' }. i
harvest# b/ w3 T8 i* l& W6 P/ q3 T
ask turtles f5 \9 T% o3 m) {
[ move-eat-age-die ]
' u* l! a* s2 m" X2 @ recolor-turtles% T5 E( C3 R+ H0 K# S' j u
if ticks mod grain-growth-interval = 0
% f$ Z# w9 ]% Q' q+ G) D [ ask patches [ grow-grain ] ]
1 q( u* F, }5 j7 k/ S$ q. \9 U ! D7 {% Q' l* Y% n. g& W- M
if ticks mod 11 = 0% _9 n7 O% _: m* x
[ask turtles( i( [5 p3 b. \
[ redistribution ]]
9 o& ?1 [' W0 y' ]; B& } ` if ticks mod 5 = 0% c1 s- m, v& v# h
[ask turtles9 H: t9 I1 }9 j* e5 |
[ visions ]]
. V7 k* w- m7 O/ a tick, Y( m+ n0 e1 F K$ _) A
update-plots9 w1 r7 d# e8 o( @/ z
end
% B B& X( e' B! s4 s0 Pto visions
3 i7 I7 n7 s- O$ O# v) ?( J set vision vision + 1
& Y/ i: `6 b8 z1 w9 \- @end
+ d* k1 U) t% N$ m: l, w& ^: c, p9 o( m4 B& h v; c
! ^* o8 \0 S1 _& \
4 w8 ~; y- o- O' c% Q$ ^: {3 N7 c7 Dto turn-towards-grain
" T3 W: l D6 E" R* M) A set heading 0
7 {8 \. m$ V* v, t& l7 E let best-direction 0
, A9 R# k& q1 _6 W3 }, u; B" v7 { let best-amount grain-ahead J: r$ Q1 t7 L) f" v( [9 ]7 h1 l
set heading 902 ]' W6 ~% M2 Y U( c
if (grain-ahead > best-amount), [ H% ?$ s3 T3 ` T) H* d
[ set best-direction 90
; `6 h" d t- e1 D1 g# H set best-amount grain-ahead ]
|4 o+ f2 f/ [ set heading 180, t9 V7 t! x7 r# j+ U# g# [
if (grain-ahead > best-amount)
1 @( V% G" Y+ m5 M& d [ set best-direction 180
! @- F1 @: w. x set best-amount grain-ahead ]9 a5 |+ O$ X) n/ ~4 E
set heading 270) G" e* [/ x+ u. h: q& ~: g1 y
if (grain-ahead > best-amount)% X1 U1 d7 C% @ j0 u/ w$ j
[ set best-direction 2702 P {; Y' } A Q
set best-amount grain-ahead ]
4 I( ^) W) q7 e" D2 q set heading best-direction& q( n5 K: d# A5 z& t$ q7 a; N
end4 f! g, \* b6 t: d
& ]5 S, V4 P. N$ ^0 @5 {
' m: Y" d5 o# Tto-report grain-ahead " \6 e8 c7 s/ t0 h
let total 0& z" g. h5 @% ]- b7 i& _. E
let how-far 1- i$ x, R' |0 R& O8 r# X! G
repeat vision; X J3 Y: n" C1 S' S3 J0 {
[ set total total + [grain-here] of patch-ahead how-far
' J( N5 r; ]' h& c; p set how-far how-far + 1 ]- r& O. }% {; c, O
report total! w2 ~* U/ Z i/ T
end: a+ Z0 t/ V4 ?
$ u; I' A" v* T- e( G! V
to grow-grain
7 z& y! ]8 ?" p q& R if (grain-here < max-grain-here)
% Z3 K+ t6 Y. G* X- I9 }( i, L# s7 M+ J [ set grain-here grain-here + num-grain-grown* T; |0 b1 R& F6 l. Q
if (grain-here > max-grain-here)
( B9 f! r2 i" A3 ]4 u [ set grain-here max-grain-here ]
* M9 i# e y5 B) k# H. H recolor-patch ]4 s2 c2 ?( I' t* S9 G. ^, I% `
end( C7 f/ [2 u. V" N0 Y+ l
to harvest
% \4 f3 f" Q' D6 T# C9 d' h ask turtles
- _ E0 T# I `9 U [ set wealth floor (wealth + (grain-here / (count turtles-here))) ]! |4 q+ s* b# G6 x' `( B
ask turtles
% G+ X2 p' L( R$ _1 G! A$ N [ set grain-here 02 L6 |) b& P; G: x
recolor-patch ]$ A9 B9 U i7 b( n, f1 }& _
6 z8 p# ~; V: e- {
end
9 Y' J4 v! c( L2 O$ i' b4 @. n6 A& A2 }. j, z
to move-eat-age-die
' D* l4 e/ E9 K1 Z fd 1
2 q& `2 R; Q( @ set wealth (wealth - metabolism)4 o! N& M- c$ d' Q
set age (age + 1)
: _( p4 m0 |" L8 L1 J ] if (age >= life-expectancy)
+ Q" T" M) i& P1 W9 B) B, D" e [ set-initial-turtle-vars-age ]
: m {. J' S2 _+ P: \ if (wealth < 0)
* t& T! u7 B& n H; G [ set-initial-turtle-vars-wealth ]6 i/ `8 T" X( Q, u! _. \
1 B: m" w; t& t! N4 H6 m6 mend# C$ m* g! Z0 T$ |4 p) f J" b
* [& p' z' d. Q! K8 M) h2 J: i0 b+ X* E. m, q- l. ]6 }) G
to setup-plots
" z6 m, T9 A8 z/ U+ M set-current-plot "Class Plot"
; t1 ?% S) o$ q8 p/ D- l2 J9 D. } set-plot-y-range 0 num-people
' f! d. H7 P$ m( K* ^ set-current-plot "Class Histogram"
5 ]2 l1 |) A& v set-plot-y-range 0 num-people
3 w- S# j* U' g' n1 t$ A3 Rend
! E4 t6 u& _: }: j4 F9 U+ ?4 A8 s9 ~; ]! d3 b. d, b) a
to update-plots" ^. ~8 @+ r" P% R4 a
update-class-plot0 N0 r4 f$ w0 Z) @+ J/ _$ m5 y2 ~
update-class-histogram
9 t ]2 J& v( ]3 \" y update-lorenz-and-gini-plots
4 F/ k9 D0 k& s: v9 c6 x# P/ xend7 J1 e0 t2 T. h; |" G; `4 l
3 g" C2 m* y) P1 E% z: @5 m- m
to update-class-plot, l# D1 l q8 u, V" }/ h
set-current-plot "Class Plot"6 d& e$ ?0 ?) k9 r) O7 h6 w( f
set-current-plot-pen "low"8 R- }6 ]% c; _% E2 j
plot count turtles with [color = red]0 M `& W8 e3 Y( R f* X' h4 k
set-current-plot-pen "mid"0 r# r7 K* l4 \, P# R
plot count turtles with [color = yellow]
3 {7 _6 V4 }) ^9 v- c4 ^! G K- t8 H set-current-plot-pen "up"! ~! H9 b5 c0 y2 |( Y
plot count turtles with [color = green]6 X: B, z' p6 N0 q
end; Q/ V6 f$ R" j
. L4 G5 }; u/ j9 w7 l# X/ e* Q9 O; a
to update-class-histogram
$ s. k/ {8 z0 u& Z- } set-current-plot "Class Histogram"
" I8 Y( V- I. z) y plot-pen-reset& _5 k3 ^$ B) q l6 c) T$ |% `
set-plot-pen-color red
4 U( u) m" F+ u0 C4 \) B6 n1 a6 c plot count turtles with [color = red]
7 p/ E( _& C2 o g- a: l" R) a set-plot-pen-color yellow6 o- R/ H( X$ q- D( {# ^
plot count turtles with [color = yellow]
2 T& S( F! O4 ~, s set-plot-pen-color green; M( s1 [* [# a' f% |7 R
plot count turtles with [color = green]
* O% E/ {5 N3 J) V2 Pend
# F+ x& P$ N \' G) Qto update-lorenz-and-gini-plots
7 \( X8 w' G7 i1 n7 p- `! m2 T set-current-plot "Lorenz Curve"' C) D8 k7 o5 Q$ W
clear-plot; {' V% b$ \0 K8 h9 |2 ^7 H) k
7 N( _5 B7 n3 m# s4 f! j1 |: [
set-current-plot-pen "equal"
( Q# d0 m H! Q. l. u w plot 0( u, p+ {- g6 q
plot 100
) g4 o# Q) T5 N# h! `
" `5 e" W" L# J9 [ set-current-plot-pen "lorenz"
1 J- S" O, m% z0 g3 b set-plot-pen-interval 100 / num-people
6 j, f" g6 ~5 ^* B plot 0
, J R8 C/ ], v$ R. n3 q7 P2 _& ]0 N7 ?9 T/ \+ O5 J9 i
let sorted-wealths sort [wealth] of turtles
" i4 Q, t* n w: }3 c! r- @ let total-wealth sum sorted-wealths
6 n9 ]! A8 O' s8 W9 l d4 Y let wealth-sum-so-far 0
& q! ~6 i) f& Q1 \4 i8 P" O6 k: a let index 0" H$ C: ^1 {8 Q! ~0 Q
let gini-index-reserve 0
' D) F0 H) h+ F: f2 y, p
- u/ Q2 a# @: v# s8 [2 m repeat num-people [! a1 s& A* O1 b9 f$ t: p0 {
set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)6 G& a5 n0 V6 l; y0 s
plot (wealth-sum-so-far / total-wealth) * 100
/ ^. m+ T6 m8 s set index (index + 1)
* F4 c' k% L7 W/ U set gini-index-reserve! d+ F; n$ y1 R3 I9 n0 H
gini-index-reserve +
8 T1 `" J. K5 Q% f9 r (index / num-people) -/ W! S; `1 i4 ]9 J
(wealth-sum-so-far / total-wealth)
/ F" ]" a& J8 ]5 F2 D ]) ?8 A6 [' \$ n
* [; \1 @( G- e2 E set-current-plot "Gini-Index v. Time"
# ^$ ]- B9 P$ F$ T plot (gini-index-reserve / num-people) / area-of-equality-triangle
) [( m5 l6 o2 [2 G. B* z( yend) S0 k7 x# B6 Q% H, C; F! j/ \
to-report area-of-equality-triangle5 q3 a' @- V# g" X0 R* J3 P
report (num-people * (num-people - 1) / 2) / (num-people ^ 2)- S @. c) N0 p: X2 M. [
end |