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
3 X; ?, J6 Q( U7 Q) k! U0 ^globals. |# v/ r' s: A4 d' D5 J
[
4 y. T l+ e; P max-grain
0 b9 f; ~. B ~$ l: r- s) e
9 q! ?" W3 {6 y v2 V]: e& j) k) w' F8 m5 q! G
; M9 }* U! h+ h
patches-own7 l- T. q8 Z4 B- v+ y4 _
[: I' g, f# P: o- u- X/ `/ y
grain-here
; `1 D) Z! M* j4 z max-grain-here ( f; q r' Q9 i4 u/ e
]" I4 }( @# P* T0 l1 Q
" @) p$ X( u, w! v) i6 Y1 f# H% tturtles-own
# ^+ [) i/ X4 u/ }$ C[& S6 r6 c8 x( Z# Z: @
age
% h) T& Y# x$ P( p0 f( t wealth 6 `: b# Y5 x: \
life-expectancy
. E9 U3 E; r' S' I, U! e# e metabolism
/ X. i* T5 ^# D" H1 a/ k9 s% `' H vision0 u% P$ ?! t6 a" h8 O
inherited
. g- H3 F6 |% u( D]
4 O/ A' R5 h0 i% \% T8 N% f
) D4 _- Q3 B) ]! q6 `1 S6 U
! \# a% I6 r4 J! t3 h3 ato setup
% }/ _+ x6 K$ d+ k' | ca+ z5 S! r8 f7 @" W
set max-grain 50' {7 B% d8 ^3 Q" g) \4 S
setup-patches0 W; k6 r9 C2 p/ s2 ?
setup-turtles3 r* G* V) V0 W5 K
setup-plots
% ?4 K" i" x) T* J update-plots
5 z5 P/ n; S/ [/ d/ ]# |3 iend
8 b3 o) a$ w0 t Z% l+ b0 p: B+ Fto setup-patches8 Q9 O: j) \8 Q4 z& {/ Y9 z0 E
ask patches
, g% u3 H; e5 t, [( ~+ } [ set max-grain-here 0* Q' n8 L9 S- H
if (random-float 100.0) <= percent-best-land. @# J# Q; }9 a/ V$ m1 {9 @8 h
[ set max-grain-here max-grain( I8 c \* d% ]* W" d/ m/ A. {
set grain-here max-grain-here ] ]
9 T |* a1 n$ H+ n repeat 51 _$ y6 D. w6 l. k7 A. I
[ ask patches with [max-grain-here != 0]% l% V( ~ J" D
[ set grain-here max-grain-here ]
! c9 C$ H7 ]- t. T& g3 P diffuse grain-here 0.5 ]0 @5 |5 R; U9 r! S8 B4 _
repeat 10
1 `. s! b( X9 J( v [ diffuse grain-here 0.5]
3 Y! z5 V% f- {( h ask patches
* p4 a, ~, e' P& ]5 z [ set grain-here floor grain-here
1 ?6 @/ u g' }6 p3 G& L2 }, T set max-grain-here grain-here
7 r! o3 T* C/ L# p/ y recolor-patch ]
6 g) q& S: G. `4 `6 A7 [- ]5 ~! D: Fend
' x+ |8 {4 F+ Q5 t8 Fto recolor-patch ; E: `* F8 ` n' w8 p/ L) Q
set pcolor scale-color sky grain-here 0 max-grain3 N" S- P. V. s" P& e* z# |3 r
end
0 N @) w, @ }' K& a* |3 ato setup-turtles- U% i8 \6 _/ @* T
set-default-shape turtles "person"
$ n7 t/ j" C+ B$ Y4 d crt num-people
7 E1 I) ^& L; [3 R1 \8 e [ move-to one-of patches
% G$ b! `" f' N# D* P' ]2 Z set size 1.5 - \- j3 y5 I" R3 z f4 A
set-initial-turtle-vars-age# R0 c* r" s x6 p r8 v/ T' G
set-initial-turtle-vars-wealth, y- w/ v1 u, N0 U) a7 l
set age random life-expectancy ]
) m! R% g c+ ?" T recolor-turtles7 z) [4 ?: Q2 Y" z( Z' @
end; R5 X/ t5 E. Z3 Q3 z9 c+ K+ g
s$ y" p& m8 n ?to set-initial-turtle-vars-age
8 W: I& [; _3 v let max-wealth max [wealth] of turtles. e% I; b' P# m* h2 j
# t' O, A' V) V0 d3 E
ifelse (wealth <= max-wealth / 3)
" k' M( v$ {4 f2 o5 o [ set color red / f9 r! t; p @* u1 j+ ^5 s
set age 0
1 i5 D( K9 ^ X, b4 s+ j0 ~+ C face one-of neighbors4
0 P5 f/ c# ^& O" D: a( i set life-expectancy life-expectancy-min +8 ?+ L: y8 |8 ]5 a7 J3 p. i* Q
random life-expectancy-max
: B0 V3 d3 g' I* _/ X. r/ t, _ set metabolism random 1 + metabolism-low
3 ^7 v/ \# e1 t' b0 M0 [0 O* ~- g set wealth metabolism + random 305 q7 z0 `; T. [
set vision 1 + random max-vision' t6 ~) D) h |% n# E, }" C7 [) g/ B
set wealth wealth + Wealth-inherited-low ]% Q/ T+ B% [6 F3 P4 b7 [
[ ifelse (wealth <= (max-wealth * 2 / 3))
- X: P' o- x) @: V4 _0 l/ w2 |3 s [ set color yellow
$ t( u+ E+ X$ y. D/ o/ g set age 0
, W9 y6 x7 j# F8 ~ face one-of neighbors4
* M; n) L/ f+ B. R' W set life-expectancy life-expectancy-min +
4 Z" P2 [4 F, v2 T5 b, T random life-expectancy-max + 1
8 S5 ~( s9 _/ \+ J set metabolism 1 + random metabolism-mid/ X$ b4 ?5 p( w% M! f
set wealth metabolism + random 30
\8 Z4 c& B8 y2 l. G set vision 3 + random max-vision
6 f2 B/ m" O7 d0 ] set wealth wealth + Wealth-inherited-mid]7 d j5 a1 e4 l6 |8 F
[ set color green
) M; [+ d+ w2 l set age 0. M* t) V+ k+ ^7 y9 Y1 W
face one-of neighbors4 # T. q' q- Q2 ^# \2 J$ n
set life-expectancy life-expectancy-min +# f# [: ~5 |/ E0 p. b
random life-expectancy-max + 2
% a# f$ E4 t& ]9 f- l: N set metabolism 2 + random metabolism-up
; Z9 r. S- O# W. g4 J5 V, V3 h$ a set wealth metabolism + random 30
) V' \; y: {" B1 b( T set vision 3 + random max-vision
/ G1 B6 n" g7 X3 j% [' e! a set wealth wealth + Wealth-inherited-up ] ] 6 c' d0 r2 }& D" u- {: Y% b
& \) J: R& c6 U% Y5 U) K
end
0 o$ n1 ^* X: t0 h L6 E7 V8 z+ ^3 eto set-initial-turtle-vars-wealth& y1 T$ V0 i# Z$ b" j E, {
let max-wealth max [wealth] of turtles
. R9 P0 ^( a3 E set age 0) a) H: L3 m; t
face one-of neighbors4 $ T7 V* j) h2 b9 ^+ {& K N
set life-expectancy life-expectancy-min +/ }; \. J* n6 Z
random life-expectancy-max 1 \4 w% v) n7 \' m0 Y, h8 P0 Y; N
set metabolism 1 + random metabolism-up7 p8 U; K3 l# A; K: z
set wealth metabolism + random 30
$ E& e3 `2 T1 q3 r% A$ a set vision 1 + random max-vision ' m- W' {9 v G$ U2 r: u6 I3 L
end
/ u& T* \; k% O) ato redistribution
0 o H" J0 F! Olet max-wealth max [wealth] of turtles1 D& V9 Q! A& S/ V) Z) h
let min-wealth min [wealth] of turtles
( z; S3 ~# b( Rif (wealth <= max-wealth / 3)
/ C1 g- q! Y% d, G5 z+ @ [set wealth wealth + Low-income-protection ]! s( M! U+ z' l. f
end. U; ~7 s% V$ B+ a6 I, {4 j1 f
! |7 z% Q2 n Z) g) C
to recolor-turtles1 U' k" K- R6 F
let max-wealth max [wealth] of turtles/ i+ U8 |' B" T# n- P* A. T
ask turtles* E1 f4 Z6 ]8 H
[ ifelse (wealth <= max-wealth / 3)
}2 U6 s/ @. C% @ [ set color red ]
4 a8 r- Y8 k' O7 U& g7 v- u [ ifelse (wealth <= (max-wealth * 2 / 3))
) Z3 O$ G. E6 x [ set color yellow ]8 T6 P$ g" g0 a: ~: Y U A; M: i# A
[ set color green ] ] ]
1 m$ ^6 T( |( r# o+ I: Q ask turtles [ifelse show-wealth?( V5 p+ _/ L) }0 T: y* H
[ set label wealth ]! A( v! |2 C: M7 z
[ set label "" ]]2 b; v2 _# T1 A& U
end7 d$ Z( d1 x# z# K- l
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to go
1 E N2 s2 [: U) |! ^; N ask turtles! r! D/ k& F& E
[ turn-towards-grain ] / ?8 y% V$ y/ R: J# {+ R
harvest
0 d) C3 u( ~, W ask turtles
8 ~& Q5 @" T7 L$ z* a. I [ move-eat-age-die ]
6 v1 v. T6 K3 t4 r; `8 i2 Q. R F$ o recolor-turtles+ t( N5 w3 c) f7 i. f
if ticks mod grain-growth-interval = 0
6 Z# ?) n; R; m [ ask patches [ grow-grain ] ]5 c% B, v, S) ]+ s+ Z
A' f& y3 `* g
if ticks mod 11 = 06 A! ?0 [( @, C7 R. b
[ask turtles
5 s" I3 o1 Y: V4 m [ redistribution ]]
6 J5 H$ B6 F% o0 a! X if ticks mod 5 = 0
5 L# Q6 Y. ~# I0 F$ m2 r! `' D [ask turtles
' Q {" a% P5 `; V6 W [ visions ]]4 B/ l# x$ M3 K+ ^
tick
& O) T8 C; X% B& j/ X6 S2 G* X update-plots: F* X# L2 I; u( P1 M# ]+ ?
end8 o( R$ D$ f( Q# u' h2 F# C8 ~7 ~
to visions
! ~2 t* y0 j8 ` z set vision vision + 1
u" }9 N5 r6 y: t, vend
8 l ~0 X# N6 A& M
' K, i8 Q Y5 L, w/ b9 ^+ }6 p& l( f9 P1 H; s- Z
( m& j. _5 n; \9 F8 W! p# e! Hto turn-towards-grain
$ T& m2 k* q2 C/ f$ f" b set heading 06 _5 N& }2 x2 c7 Y! u
let best-direction 0
/ P" Q4 \2 ?, l6 R* X( B& u let best-amount grain-ahead9 P+ ^( h8 A2 j
set heading 90
6 P0 X( g# d7 U3 B5 l, S if (grain-ahead > best-amount)
" P1 o3 c* I& [& }( g [ set best-direction 90
4 e+ l4 c1 l- n( H; h5 ?* F set best-amount grain-ahead ]7 O5 `% A8 V. U
set heading 180
7 y1 Y& m" J, M0 Q6 {, Z if (grain-ahead > best-amount)0 S: e- a t' E2 j: ]
[ set best-direction 180: P4 a6 e9 C' R( M3 F, \
set best-amount grain-ahead ]2 E8 x( e2 f4 Y$ [ @7 V
set heading 270
% T8 M' q( @2 u7 v$ L: ^ if (grain-ahead > best-amount)8 B9 b% J. S" \/ d. O
[ set best-direction 270
. ]+ o" R6 R; r3 X2 N E set best-amount grain-ahead ]& _$ a) J, R8 R7 f+ O
set heading best-direction
3 {0 D$ F' r. n# r: H6 g$ ~end$ S3 B4 k* Y( k. \) h
8 P8 S3 W; N( E* J
+ _3 n# E) J6 _
to-report grain-ahead + k6 Y2 u/ ~& e& V
let total 0
% Z; f2 Y" c5 Q8 j; ^ let how-far 1* A7 z) Y9 L9 Z, q0 z
repeat vision: |6 k- g. ? ?. x! X- a1 U
[ set total total + [grain-here] of patch-ahead how-far
: d `4 u4 ~3 W8 ]- e) ?* _& b set how-far how-far + 1 ]4 _& Z+ Y% D! D: Z
report total4 [6 v, n; i3 W
end
Z/ S: D" K2 x, J: `% D
) z" O$ Y2 P% k$ R' Lto grow-grain ; G" |0 b0 Y' ?4 z2 S
if (grain-here < max-grain-here)1 f& u% _! X$ H8 C4 p- Z
[ set grain-here grain-here + num-grain-grown
# d; }4 Y- @( g% T4 D- V0 m( p Q. c if (grain-here > max-grain-here)
2 I/ D, L6 i/ ?* v [ set grain-here max-grain-here ]
% }4 e B+ ]# _- t2 K" g+ Y: | recolor-patch ]4 b7 q- B4 h2 t. x$ E! d l! W
end6 i) p/ d7 T/ ~( B: z* B2 h
to harvest/ M) [- y, T6 j d
ask turtles0 \4 C _) M; E8 i8 W. L( f
[ set wealth floor (wealth + (grain-here / (count turtles-here))) ]0 X! [* `+ W* K( s/ t$ ?2 R" ]6 S
ask turtles
8 P! ^. t4 T( i1 L$ v+ r [ set grain-here 0
# F- ~" U* t8 [7 S recolor-patch ]! A: O/ e* k$ n! {
8 y, h5 x+ ?3 ~+ I' |
end4 A2 N, k/ S% f$ p6 T' l& L" h5 B
4 ` \" C$ h+ w i- J, Zto move-eat-age-die
) l7 f: }5 Y2 z* T) `, P fd 1
- x1 D0 r* t! k6 z) Z9 A! }, m set wealth (wealth - metabolism)+ W; X4 j/ K% K( V
set age (age + 1). `! E9 y. e+ p7 s( |; v) z# U
if (age >= life-expectancy)
( w# R8 t: a+ n& _3 x J, j0 y5 ?& A [ set-initial-turtle-vars-age ]' h0 x0 p5 \; J- P4 w
if (wealth < 0)- x4 a6 l" C6 ^( v/ w: X
[ set-initial-turtle-vars-wealth ]
" m' f/ U# d6 y* k- O, T & m8 p* F8 l, x$ g& G
end; Q7 s! q( H% n
. C; ~" `, v! k+ O+ E' p/ I k0 @ a2 o3 H' p6 }
to setup-plots" C1 g K; C- ?3 F" E0 v' c- Z
set-current-plot "Class Plot"
- @0 d! F! n0 {/ ^0 u4 b/ o set-plot-y-range 0 num-people" R- u5 e+ @( Y7 n5 L& w
set-current-plot "Class Histogram"$ d# @/ s. c Y `6 a3 H
set-plot-y-range 0 num-people, ]; F6 Z2 l8 H
end
S1 L" s2 T3 ?4 h( O, n B
" u( K: E1 Q6 V( F; Eto update-plots
6 i+ \* V! r) j ]9 E3 Y# ~- A update-class-plot; A! l9 x9 d/ J9 r: U6 l$ @! j
update-class-histogram
0 F& u; k/ n" Y' G# H update-lorenz-and-gini-plots; O7 x5 N0 t4 ^8 `
end
- v# V/ x2 X8 D% i" h8 R# J5 Q, d' G$ y' p) Y5 n5 b
to update-class-plot
2 f8 I0 X: }0 R0 \# {' _) Z& k set-current-plot "Class Plot") ?& {* ?' o' y
set-current-plot-pen "low"2 M6 o1 Z3 T5 J+ r
plot count turtles with [color = red]
1 G7 w0 g3 Q% K _$ I set-current-plot-pen "mid"$ N+ E& F# c s6 K/ J' [! F
plot count turtles with [color = yellow]+ Q2 H0 k" ?4 ]( o% d
set-current-plot-pen "up"
8 x3 {9 Y) Y; G1 p plot count turtles with [color = green]+ o/ M+ d1 e% ?8 Q1 t2 {8 h
end1 B2 t2 c5 v* ]' p9 C ]) O
# F1 x- N6 D% x7 N+ E
to update-class-histogram
( \1 V& s( |! z7 i# G7 O0 E set-current-plot "Class Histogram"
. N. K9 Q3 ]. i# i, Z$ q plot-pen-reset
4 h5 H; y! s8 F set-plot-pen-color red& x6 Y Z( S% D
plot count turtles with [color = red], i) H7 Z, j" a" \ [
set-plot-pen-color yellow
- m4 h: e0 c: g7 ?) s plot count turtles with [color = yellow]
' d, F, m8 V$ G) I set-plot-pen-color green
~' p5 _! n& W' ^ plot count turtles with [color = green]; E6 C4 [9 {' L# s2 x
end
/ d# j% z% {2 y! j( kto update-lorenz-and-gini-plots
) t S3 F, w f; u1 v set-current-plot "Lorenz Curve"
& ~( |- u; F3 e clear-plot
# N; j" d6 F) O5 q2 p! O( I: g
# r9 i8 b9 f% d- x set-current-plot-pen "equal"
! e4 T+ a; r; d- B% H: n plot 0
; ~" x1 {% o0 U2 r, O plot 100
6 J7 C0 V3 k+ {9 `9 r
% L7 V- D' @( e" P9 j2 a, U set-current-plot-pen "lorenz"/ j% s$ _1 a0 Z. O
set-plot-pen-interval 100 / num-people
% ~( e" Y" i. ^0 m3 P plot 0; H1 B* \; V2 R$ d! M' [
& W3 w2 G6 P1 a0 F3 N5 Q+ x4 J8 H let sorted-wealths sort [wealth] of turtles
' B; Y) E, d' ], |6 ?3 y U let total-wealth sum sorted-wealths
! N( |2 u, L; j- b let wealth-sum-so-far 0& m8 E9 `6 Y" V1 T9 c8 i! [
let index 0
/ \& C& C! A% a. j f let gini-index-reserve 0) ]/ A% R* W) ~; ]
* |4 ^& P, Z4 L0 K% R
repeat num-people [
]- {* c6 g2 {) R) p; T set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)1 W7 O3 ]. Z, J
plot (wealth-sum-so-far / total-wealth) * 1009 Y/ L! W$ x i! _! h
set index (index + 1)
1 e: k& s+ Z, w. ^6 T; m; t2 w set gini-index-reserve" Z5 h6 _( m0 `7 I
gini-index-reserve +
2 o4 ]2 U3 w4 \* X, l (index / num-people) -
& s. d8 t) v0 Q1 s" ? (wealth-sum-so-far / total-wealth)
# K1 E- Q8 H- D' T3 O ]
% R& l5 w1 W6 E4 b' i8 \# R& a* c! d: f" ~+ O$ w& c: A- ^
set-current-plot "Gini-Index v. Time"3 Z' S, ]9 r( F. a# s* y
plot (gini-index-reserve / num-people) / area-of-equality-triangle
5 d% V0 i3 u1 rend
2 S* B. @+ D+ E+ f9 M$ Vto-report area-of-equality-triangle
- v, g* E9 O/ {' _ report (num-people * (num-people - 1) / 2) / (num-people ^ 2)
7 U2 C" X; D# X2 o fend |