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& B8 K) }, ?8 I9 R3 K! z. A
globals
7 O1 }7 U# L. _" k; c[
4 a8 K( H) [' `9 V1 t max-grain
* V+ K6 \/ L2 F1 y& F) Q3 W: f- }. F. }
]
' b4 ]% q4 b0 F3 v) @, L
' h) @! P) G6 T7 F0 o# u5 u0 Hpatches-own
7 B* H) ~. E7 V* c3 q+ i9 P[9 \8 ?8 |5 ^$ z3 O1 D- f2 u" V7 P8 R
grain-here 2 f) {8 N* ? f" W$ a9 R
max-grain-here 1 X/ B% h1 h1 M1 B; @/ j; c
]
5 c: \% T! H, ^. I* h& j. o3 m9 n4 A2 L9 Q* u: J4 ^, d5 r1 K
turtles-own
% S* Q# Z. P1 L! C1 H- J[
! ?. b- J; e2 z$ v X" y! X age
& Z! U$ D& A; Z9 \1 V0 b. z- Y wealth
% G* Q5 h% m$ e7 j) A0 ^3 t' z, w life-expectancy $ W) k! z) _4 t
metabolism
Q7 l/ O& t6 {# u0 v3 Z vision8 P y8 l1 ` G/ \/ r0 s `9 f0 @$ x/ q
inherited
+ U- N- ]( h5 c. ?]4 D0 D* Z1 ~" K& E7 H
C' _" M- ~3 R+ W: G; v
6 i; Q( T j9 ~% L5 Hto setup
* H+ Z. P: d z2 B2 @$ S9 D ca
. I7 u! ~9 N" I8 Y5 i set max-grain 505 E( K: v+ v( m. ~) k
setup-patches
$ _/ r: W$ V% \" F+ Y7 j$ J+ u, D5 D setup-turtles
6 H4 Q, h: t( X8 g! L setup-plots8 S; H) o( A0 \* ]$ ^
update-plots
0 r7 [$ g8 T! bend- E% f9 O! \4 h4 z
to setup-patches/ V: p5 i" X$ H
ask patches& j8 U4 x3 z5 l* U9 g5 R, C; F
[ set max-grain-here 0 }' }% t$ m3 e, C5 s* {
if (random-float 100.0) <= percent-best-land
1 Z# U" W9 d' I; ? [ set max-grain-here max-grain
0 a7 ]6 f( A" V8 L5 Y) W set grain-here max-grain-here ] ]9 e! H$ I8 o$ k' \9 C0 i2 U# ~
repeat 5# d" p8 R, F' [" b; M0 q6 k1 U8 J
[ ask patches with [max-grain-here != 0]
3 f& f$ e- T. Q2 |2 b2 o+ }0 B {6 z [ set grain-here max-grain-here ]" @" p% d# y7 s; R/ P- ?. \
diffuse grain-here 0.5 ]
- t/ ~7 I8 _7 v. b6 J- F! H repeat 10
& T- o) B8 g9 V" O; e [ diffuse grain-here 0.5] 1 r% N1 B# B% b0 e
ask patches
- B8 M8 o& `6 I4 [ H [ set grain-here floor grain-here : t/ w1 t. f) `0 W2 ?) @
set max-grain-here grain-here
9 c$ L$ ~& X j$ d% l' j$ l recolor-patch ]
X. R" e4 z8 ]! z: t6 N% z8 [$ wend
0 v5 f4 u! N6 P' ]to recolor-patch , V* [) {8 U+ f! ~7 y8 W
set pcolor scale-color sky grain-here 0 max-grain5 G! e# O1 |% | h
end
& @+ Y+ y ]& v$ {+ D/ mto setup-turtles; {& i% b, C7 S; v
set-default-shape turtles "person"; u6 p1 u I* }) ~4 Z& }/ W5 m
crt num-people: j: `7 w9 o1 M& i
[ move-to one-of patches ( X. H }: p$ v
set size 1.5 4 F# u9 ^7 P- k) s2 H2 q4 h
set-initial-turtle-vars-age
" Z3 g; n* S3 s set-initial-turtle-vars-wealth
% K! l# s9 h' [# K" f/ E set age random life-expectancy ]
& U( J6 Q+ \1 J7 b/ A/ K8 r recolor-turtles
, V% a( q/ ^3 i) uend
4 w/ ]! F$ L) ]' T8 Y/ Z u/ E( Q% o3 Z1 T" V C" O, j$ E0 K
to set-initial-turtle-vars-age
2 l! L( ]4 o# @' d p1 C let max-wealth max [wealth] of turtles
! Q7 p D5 d: X( m }' [% P9 M) D0 |
8 m2 O1 Y1 t/ L ifelse (wealth <= max-wealth / 3)
' t" h/ m }. [+ l: h. w [ set color red ' A& X) r0 `' V( q/ V
set age 04 u7 b0 m7 H) I+ g p7 v
face one-of neighbors4 0 u9 t. u# T7 F: A, z* G7 m- l
set life-expectancy life-expectancy-min +
0 N) \+ q6 h: K0 k random life-expectancy-max * W. }0 x. O- z
set metabolism random 1 + metabolism-low
1 H1 A$ l: e# ~/ G set wealth metabolism + random 30
; H7 B+ z- r% [* l set vision 1 + random max-vision
# x; V' t- Z+ H p& ?7 ?4 d. d! y set wealth wealth + Wealth-inherited-low ]
: L% w1 h8 S& G* ]) u [ ifelse (wealth <= (max-wealth * 2 / 3))
' P) c* Z; }4 i) Y [ set color yellow
c/ X' M& @' ^: {9 m: e' U set age 0
c% @# o( U, S7 b# Z% M face one-of neighbors4 ' U) ?1 ?# m3 Z0 I
set life-expectancy life-expectancy-min +" ^+ {% S5 _' O' v0 u7 Q
random life-expectancy-max + 1
' C- h) U9 P! s1 {; M- w set metabolism 1 + random metabolism-mid) @$ n: i4 r2 `
set wealth metabolism + random 30. R# G3 f+ Q7 T% m( J/ _1 }; w
set vision 3 + random max-vision# h5 M( [: y$ _# T/ r: ^8 o
set wealth wealth + Wealth-inherited-mid]+ O8 r; B5 v0 V0 C
[ set color green & Y, s) g8 V4 \4 v
set age 0% Q% W! u0 P. k/ V! k6 x* @
face one-of neighbors4
1 ~% O O2 O1 j/ `1 m1 b set life-expectancy life-expectancy-min +7 r' z' |1 \# H1 _5 r1 B1 h
random life-expectancy-max + 2
! y1 |$ p0 N. M* ~" W/ Q1 t; b set metabolism 2 + random metabolism-up" b5 [3 |6 w: W) a/ }
set wealth metabolism + random 30
6 r: f2 N8 g, {( p9 ~- d set vision 3 + random max-vision9 ~( H2 r/ z' l6 c6 p2 a
set wealth wealth + Wealth-inherited-up ] ] 5 D& Z' p! b6 O: N4 S+ @9 r
% K/ |. X, G, S; k% X
end
8 Z; L l3 Z$ l: C( x9 wto set-initial-turtle-vars-wealth( b- r2 W, C. e! j
let max-wealth max [wealth] of turtles
$ [7 n) Y7 E+ O- M2 ~) ~ set age 0% b; U# G+ t& k0 A" G) v. _
face one-of neighbors4 - {7 K1 H2 x8 F2 ~
set life-expectancy life-expectancy-min +
, U# g' ?, K: O8 l H! C random life-expectancy-max
' I" f. H) i. J4 D9 V set metabolism 1 + random metabolism-up
) l" e5 ~& \+ @! ~6 }6 m. M set wealth metabolism + random 309 Y9 D$ \& y, H7 z# S
set vision 1 + random max-vision & E0 T9 P1 V3 M" w) P
end
. e( z- Y2 `. e. t* C$ e7 Rto redistribution
: C3 ]2 \3 r6 |/ [2 V) Blet max-wealth max [wealth] of turtles
+ z: M( F2 I! ?9 w0 ]let min-wealth min [wealth] of turtles1 w$ x( t+ W" k4 b) h
if (wealth <= max-wealth / 3)( m" P, H' O2 ]3 _" E `# j
[set wealth wealth + Low-income-protection ]
% s, w8 P& i& d6 K" k" fend
n3 {9 y V4 `# y$ n
4 a5 m. n) s' lto recolor-turtles% H+ R: T- T: U" c7 G
let max-wealth max [wealth] of turtles
6 l& T' i) e- I& H+ F- Z- C; W ask turtles
, P) w* A3 C$ W; ~ [ ifelse (wealth <= max-wealth / 3)
" g w& }4 F: G! K: `; @ ] [ set color red ]
) E" N) j3 |& [. x( i# Y* G [ ifelse (wealth <= (max-wealth * 2 / 3))1 R! c7 g" A4 c, [2 Q* ^9 s$ t
[ set color yellow ]
' a& Z+ O7 R0 o- _ }+ W# k5 @ [ set color green ] ] ]
4 T" h! |- P- S ask turtles [ifelse show-wealth?
1 [' Z0 L# M- ^; ? [ set label wealth ]
5 Y7 f0 @* ?* N4 s, D/ @8 n [ set label "" ]]4 a8 g+ O7 l7 R2 z8 ?
end/ M# ?" B# E, J) z( i* B6 {8 e
" ^: x; H) K) S, ?: ~7 z) `7 t
to go3 D; }* {4 K( C6 R- K3 G: J/ [$ H
ask turtles2 I" i, K! T+ ?8 L8 E7 j S
[ turn-towards-grain ] ) a2 `/ P9 X/ F( X' r! m/ W! _
harvest
) t2 p$ k, E8 r& W" R* N2 ^ ask turtles
# C+ E2 z+ A7 q1 O [ move-eat-age-die ]) s8 ]7 K; `7 S
recolor-turtles
" E' {$ y' g3 c+ r if ticks mod grain-growth-interval = 0
. t& p. l: j1 x( \* ]. ?+ z! [4 K2 { [ ask patches [ grow-grain ] ]
" i0 {6 F# Y8 Q
% [7 I! Z7 l6 p6 A9 K, F if ticks mod 11 = 0
* o# F6 @" }' i2 U5 i# Z [ask turtles
% N# G6 @& D+ U8 L: k- V5 I, F [ redistribution ]]+ M$ o) W% N* I, T2 D/ `) m, k% h( Y
if ticks mod 5 = 0
* _- d8 N6 Y4 Y1 Q' @/ M6 ]8 P5 H [ask turtles
% r' k! g: H1 |4 x6 q [ visions ]], m, I& S0 R. {! n9 e3 j5 V: @0 m, K
tick0 [8 ^/ m! K/ R+ j: o0 s# s. Y: {7 C
update-plots
' l; h7 w: W; z/ Eend$ q) `5 K/ m3 B- l" D/ w
to visions' X0 ^8 l5 h: e Q8 h! C" q, H R8 z2 D
set vision vision + 1 5 \5 C! m7 w; c! M) |% C: A
end
5 N2 e4 q n' |8 L+ ?2 i2 w3 c1 e |3 L8 n0 h8 w$ M9 o' j
2 n- B$ |# t* b2 d1 N- R+ N' T! `) I
to turn-towards-grain
2 h( C2 }/ d, D# ~6 P; y" L0 [& W set heading 0
8 e) v0 Y* i9 V* _ let best-direction 06 d3 j3 b& E5 z9 W7 @5 X
let best-amount grain-ahead
# L3 \* U/ d: C8 I set heading 90
& l) d3 u' I. l if (grain-ahead > best-amount): Q# y% Z$ z: A2 p. c( ]* P, g
[ set best-direction 90- E$ ?. p, b7 E
set best-amount grain-ahead ]# P1 ]* m0 s/ x7 E3 q* J5 c8 V; D
set heading 180
3 |: x+ S5 r# u8 k if (grain-ahead > best-amount): A- b& H# v- g; u: t" V. I; D
[ set best-direction 1804 h) b+ G1 M2 o( V
set best-amount grain-ahead ]
, B' o& _! J) [" i& K: \% p3 | set heading 270. i; f# `& u7 g z% E+ J
if (grain-ahead > best-amount)
- O8 }7 z) p; }; D [ set best-direction 2706 |8 ]9 h6 C z! P, Z
set best-amount grain-ahead ]* p4 x% L' t7 F6 Z
set heading best-direction8 ?$ b- C. v/ T+ D8 {5 }% u/ B
end
8 c$ m6 h1 q( m) l0 k3 H1 B6 f$ j' k+ r4 D) K% a j
0 H" [5 M* e5 p3 j, S5 b
to-report grain-ahead
2 z7 `3 F0 y7 d( e let total 0
* U* }" D) g+ C- k let how-far 12 d0 l; ^ V, x" `: l1 s& s9 N
repeat vision, b- v1 F+ G0 C( n( t8 l, y
[ set total total + [grain-here] of patch-ahead how-far
) C U. `% K3 C( B, }) t1 f) |6 ? set how-far how-far + 1 ]# [ {. j2 W, ]8 i6 N/ {' t7 S9 C
report total
' K' C/ p% q+ `; xend5 \" N( G5 z; L' K. J3 a
5 c* T2 _: ~1 \& v9 W: }3 u" Q
to grow-grain ; J9 w/ Y0 N b
if (grain-here < max-grain-here); A* d# m8 I% ^/ v" z7 D! h& ~* ]; m
[ set grain-here grain-here + num-grain-grown; T G f7 l9 k! j" T" k
if (grain-here > max-grain-here)
- ] k9 E% Y9 [ [ set grain-here max-grain-here ]
0 d/ k* f* z7 L: |+ f3 f& l. U recolor-patch ]
7 ~* U/ f1 ^# y( cend
* b' M- E1 u& eto harvest0 B8 A) _/ Q. {+ \* @" c0 L
ask turtles" g3 ?* C1 {8 v
[ set wealth floor (wealth + (grain-here / (count turtles-here))) ]- d/ f8 |4 N% M$ e1 W% N. a q
ask turtles
3 G' X( h7 b$ l m3 x1 Y' v4 S7 j: @ [ set grain-here 03 ]) ?( z& o) b( R* @2 Y( T
recolor-patch ]
! m! s1 \. z. [; ?% P
% F4 ~- e+ y) {- Yend
/ ~2 A( ~3 z; {9 Y6 y% X/ c6 h0 U Q" \
to move-eat-age-die 1 {; E% H6 M0 a+ T
fd 1
, N) U: I0 `* A set wealth (wealth - metabolism)( c0 B0 w# t/ }2 w* N% k
set age (age + 1)) Z; R/ l+ l3 o& p
if (age >= life-expectancy)' o1 N6 p6 W" Q/ ~; l7 B' h- B) P! a" {
[ set-initial-turtle-vars-age ]
( w' L- w+ K& e if (wealth < 0)5 P8 \. Y7 E" |# A2 S
[ set-initial-turtle-vars-wealth ]# p. Z+ U1 V" N( a1 I6 e( C/ m. x
p) S- }8 M z& d* Q1 b' R# ^ \end
$ R+ Q! U8 X: `3 M5 u% B- ?1 B4 r8 t' ^' |) R
; N8 e# E2 } P2 qto setup-plots+ }# n: w2 p' u
set-current-plot "Class Plot"
5 R4 N6 S, T: u% n+ _( I$ \7 l! p set-plot-y-range 0 num-people
. y9 S) R* g4 I( E2 ^ set-current-plot "Class Histogram"
( M: B: p, U9 H# x1 G4 E4 m/ \ set-plot-y-range 0 num-people( u( K6 x" y& z
end
* |0 o* W+ e6 Z/ o& N5 `$ F3 G# [! k6 M8 a/ n0 q) C
to update-plots
( p s2 j: R( c update-class-plot" ?$ Y+ d8 t) J! F; [: f' r9 F
update-class-histogram- [2 L& [" O8 \
update-lorenz-and-gini-plots/ ^: c" a9 r. |7 Q0 W7 \
end
- G W( k# B0 g/ J h& L" c" H( D6 u$ c& Y4 y4 \! z
to update-class-plot' Z+ W$ d4 k! b0 {. K
set-current-plot "Class Plot"; |3 s0 s+ Z/ L$ O% J! `6 X$ A
set-current-plot-pen "low"
) ~: R. O9 r: x plot count turtles with [color = red]% z+ y ?: y5 K% r; d8 d$ b4 m
set-current-plot-pen "mid"6 B' J4 z q' q& r/ X" O3 R/ M" s3 f
plot count turtles with [color = yellow]. f% t" _# K& l/ G$ h
set-current-plot-pen "up"' Y! o j: u8 ^5 L
plot count turtles with [color = green]
% I8 f: W" b) x7 P8 Jend
6 }. G6 e5 T4 n, G8 g6 B
# p# Q6 ?3 P- F% b; Q8 C) K: uto update-class-histogram# [; i( ?0 q+ l: P7 Q; a0 ^
set-current-plot "Class Histogram"
( x* r1 f, O8 l; u h) p0 S l% } plot-pen-reset0 d& F& X6 W3 Q# w6 ] L0 F
set-plot-pen-color red3 _2 k& `4 z" O+ h5 ~ q* `4 X0 d2 ^
plot count turtles with [color = red]* @: L" I4 f6 \- c5 n9 g
set-plot-pen-color yellow
% E- I" [2 y3 k) P plot count turtles with [color = yellow]- W& L5 j+ x" q; x, B9 k
set-plot-pen-color green, d+ i1 g. C+ l8 V4 k" H
plot count turtles with [color = green]3 ~: b, n9 J5 i( v( X/ ^( Q8 ^
end
( ~2 {3 o: i H9 e' eto update-lorenz-and-gini-plots7 F: C0 q" Y# V8 J* [) `
set-current-plot "Lorenz Curve"% w$ t% V! H, j
clear-plot+ X2 r) N1 w: n, L- l
9 c5 D' I! F/ p l- j
set-current-plot-pen "equal"
( w# S! ~$ n! d9 C' r2 ]0 n plot 01 v/ }" g. }$ c) m! r
plot 100
1 D U2 k* N" {$ M
& C9 k0 @" F. T0 H- I, U set-current-plot-pen "lorenz"& H9 w% T' e- g7 L+ X
set-plot-pen-interval 100 / num-people
+ f' c: `; l( C6 | plot 0 ?/ ^3 g) f9 {( B
% e3 g, u- p+ H. Q* Z w let sorted-wealths sort [wealth] of turtles, W: @. H* E# a
let total-wealth sum sorted-wealths" v. P. b, B" Z- ]4 j
let wealth-sum-so-far 0& h$ i0 y J/ E
let index 00 ~# {' a' T5 ^" \
let gini-index-reserve 0! ~& ~+ X2 G% D, y5 Z6 j; W
3 z2 U+ U, R# E; N* R6 k! q4 C2 a repeat num-people [# X+ m0 _+ w/ c8 e7 r& |* a
set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)0 V) N% x( c7 i. m+ j8 [) ]$ M3 i
plot (wealth-sum-so-far / total-wealth) * 100% G h! `* K2 g
set index (index + 1)9 W2 S' P/ p* X# B9 X0 O. o3 g
set gini-index-reserve' _. {5 u- x9 M: G: d3 D+ e6 c4 A
gini-index-reserve +
7 h. k* A, d5 `3 X (index / num-people) -, h2 n% b4 I# u
(wealth-sum-so-far / total-wealth). w; T5 a5 l8 {5 B2 \7 u3 U. d
]1 C5 J. L- p% Y" Q) q
% G4 b$ t, ~0 a6 W
set-current-plot "Gini-Index v. Time". ~% [& J4 Z3 H- n3 x0 H2 K$ f
plot (gini-index-reserve / num-people) / area-of-equality-triangle% N3 e' X, K0 P# W4 Z0 {
end' I' D, n: C! x1 o
to-report area-of-equality-triangle, O! X# w% U+ F+ ]1 H5 N' t6 ^& B, r
report (num-people * (num-people - 1) / 2) / (num-people ^ 2)9 Y6 C* j' |" W1 A7 r$ R+ w
end |